Matlab 函数分类汇总-R2011b版

Function Reference

File I/O Data Organization Descriptive Statistics Statistical Visualization Probability Distributions Hypothesis Tests Analysis of Variance Parametric Regression Analysis Multivariate Methods Cluster Analysis Model Assessment Parametric Classification Nonparametric Supervised Learning Alphabetical List Class Reference

Data file input/output Data arrays and groups Data summaries Data patterns and trends Modeling data frequency Inferences from data Modeling data variance Continuous data models Visualization and reduction Identifying data categories Identifying data categories Categorical data models Classification and regression via trees, bagging, boosting, and more Stochastic data models Systematic data collection Production monitoring Interactive tools General purpose Hidden Markov Models Design of Experiments Statistical Process Control GUIs Utilities File I/O

caseread casewrite tblread tblwrite tdfread

Read case names from file Write case names to file Read tabular data from file Write tabular data to file Read tab-delimited file

1

xptread

Create dataset array from data stored in SAS XPORT format file

Data Organization

Categorical Arrays Dataset Arrays Grouped Data Categorical Arrays

addlevels

(categorical) categorical cellstr

(categorical) circshift

(categorical) ctranspose (categorical) double

(categorical) droplevels (categorical)

Add levels to categorical array

cat (categorical) Concatenate categorical arrays

Create categorical array

Convert categorical array to cell array of strings

char (categorical) Convert categorical array to character array

Shift categorical array circularly Transpose categorical matrix

Convert categorical array to double array Drop levels

end (categorical) Last index in indexing expression for categorical

array flipdim

(categorical) fliplr

(categorical) flipud

(categorical) getlabels

(categorical) getlevels

(categorical)

Flip categorical array along specified dimension Flip categorical matrix in left/right direction Flip categorical matrix in up/down direction Access categorical array labels Get categorical array levels

2

hist (categorical) Plot histogram of categorical data horzcat

(categorical) int16

(categorical) int32

(categorical) int64

(categorical)

Horizontal concatenation for categorical arrays Convert categorical array to signed 16-bit integer array

Convert categorical array to signed 32-bit integer array

Convert categorical array to signed 64-bit integer array

int8 (categorical) Convert categorical array to signed 8-bit integer

array intersect

(categorical) ipermute

(categorical) isempty

(categorical) isequal

(categorical) islevel

(categorical) ismember

(categorical) isscalar

(categorical) isundefined (categorical) isvector

(categorical) length

(categorical) levelcounts (categorical) mergelevels (ordinal) ndims

(categorical) nominal numel

(categorical)

Set intersection for categorical arrays

Inverse permute dimensions of categorical array True for empty categorical array True if categorical arrays are equal Test for levels

True for elements of categorical array in set

ismember (ordinal) Test for membership

True if categorical array is scalar Test for undefined elements

True if categorical array is vector Length of categorical array Element counts by level Merge levels

Number of dimensions of categorical array Construct nominal categorical array Number of elements in categorical array

3

ordinal permute

(categorical) reorderlevels (categorical) repmat

(categorical) reshape

(categorical) rot90

(categorical) setdiff

(categorical) setlabels

(categorical) setxor

(categorical) shiftdim

(categorical) single

(categorical) sort (ordinal) squeeze

(categorical) summary

(categorical) times

(categorical) transpose

(categorical) uint16

(categorical) uint32

(categorical) uint64

(categorical) uint8

(categorical) union

Construct ordinal categorical array Permute dimensions of categorical array Reorder levels

Replicate and tile categorical array Resize categorical array

Rotate categorical matrix 90 degrees Set difference for categorical arrays Label levels

Set exclusive-or for categorical arrays Shift dimensions of categorical array Convert categorical array to single array

size (categorical) Size of categorical array

Sort elements of ordinal array

Squeeze singleton dimensions from categorical array Summary statistics for categorical array Product of categorical arrays Transpose categorical matrix

Convert categorical array to unsigned 16-bit integers Convert categorical array to unsigned 32-bit integers Convert categorical array to unsigned 64-bit integers Convert categorical array to unsigned 8-bit integers Set union for categorical arrays

4

sortrows (ordinal) Sort rows

(categorical) unique

(categorical) vertcat

(categorical)

Unique values in categorical array

Vertical concatenation for categorical arrays

Dataset Arrays

cat (dataset) dataset datasetfun (dataset) end (dataset) get (dataset)

Concatenate dataset arrays Construct dataset array

Apply function to dataset array variables

cellstr (dataset) Create cell array of strings from dataset array

double (dataset) Convert dataset variables to double array

Last index in indexing expression for dataset array Access dataset array properties

export (dataset) Write dataset array to file

grpstats (dataset) Summary statistics by group for dataset arrays horzcat (dataset) Horizontal concatenation for dataset arrays isempty (dataset) True for empty dataset array join (dataset) Merge observations

length (dataset) Length of dataset array ndims (dataset) numel (dataset) replacedata (dataset) set (dataset) size (dataset) stack (dataset)

Number of dimensions of dataset array Number of elements in dataset array Replace dataset variables Set and display properties Size of dataset array

Stack data from multiple variables into single variable

single (dataset) Convert dataset variables to single array sortrows (dataset) Sort rows of dataset array

summary (dataset) Print summary of dataset array unique (dataset) Unique observations in dataset array

unstack (dataset) Unstack data from single variable into multiple

variables vertcat (dataset) Vertical concatenation for dataset arrays

Grouped Data

5

gplotmatrix grp2idx grpstats gscatter

Matrix of scatter plots by group

Create index vector from grouping variable Summary statistics by group Scatter plot by group

Descriptive Statistics

Summaries Measures of Central Tendency Measures of Dispersion Measures of Shape Statistics Resampling Data with Missing Values Data Correlation Summaries

crosstab grpstats summary

(categorical) tabulate

Cross-tabulation

Summary statistics by group

Summary statistics for categorical array Frequency table

Measures of Central Tendency

geomean harmmean trimmean

Geometric mean Harmonic mean

Mean excluding outliers

Measures of Dispersion

iqr mad moment range

Interquartile range

Mean or median absolute deviation Central moments Range of values

6

Measures of Shape

kurtosis moment prctile quantile skewness zscore

Kurtosis Central moments

Calculate percentile values Quantiles Skewness

Standardized z-scores

Statistics Resampling

bootci bootstrp jackknife

Bootstrap confidence interval Bootstrap sampling Jackknife sampling

Data with Missing Values

nancov nanmax nanmean nanmedian nanmin nanstd nansum nanvar

Covariance ignoring NaN values Maximum ignoring NaN values Mean ignoring NaN values Median ignoring NaN values Minimum ignoring NaN values

Standard deviation ignoring NaN values Sum ignoring NaN values Variance, ignoring NaN values

Data Correlation

canoncorr cholcov cophenet corr corrcov partialcorr tiedrank

Canonical correlation

Cholesky-like covariance decomposition Cophenetic correlation coefficient Linear or rank correlation

Convert covariance matrix to correlation matrix Linear or rank partial correlation coefficients Rank adjusted for ties

Statistical Visualization

7

Distribution Plots Scatter Plots ANOVA Plots Regression Plots Multivariate Plots Cluster Plots Classification Plots DOE Plots SPC Plots Distribution Plots

boxplot cdfplot dfittool disttool ecdfhist fsurfht hist3 histfit normplot normspec pareto probplot qqplot randtool scatterhist surfht wblplot

Box plot

Empirical cumulative distribution function plot Interactive distribution fitting

Interactive density and distribution plots

Empirical cumulative distribution function histogram Interactive contour plot Bivariate histogram Histogram with normal fit Normal probability plot

Normal density plot between specifications Pareto chart Probability plots Quantile-quantile plot

Interactive random number generation Scatter plot with marginal histograms Interactive contour plot Weibull probability plot

Scatter Plots

gline gname

Interactively add line to plot Add case names to plot

8

gplotmatrix gscatter lsline refcurve refline scatterhist

Matrix of scatter plots by group Scatter plot by group

Add least-squares line to scatter plot Add reference curve to plot Add reference line to plot

Scatter plot with marginal histograms

ANOVA Plots

anova1 aoctool manovacluster multcompare

One-way analysis of variance Interactive analysis of covariance

Dendrogram of group mean clusters following MANOVA Multiple comparison test

Regression Plots

addedvarplot gline lassoPlot lsline polytool rcoplot refcurve refline robustdemo rsmdemo rstool

view

(classregtree)

Added-variable plot

Interactively add line to plot Trace plot of lasso fit

Add least-squares line to scatter plot Interactive polynomial fitting Residual case order plot Add reference curve to plot Add reference line to plot Interactive robust regression

Interactive response surface demonstration Interactive response surface modeling Plot tree

Multivariate Plots

andrewsplot biplot glyphplot parallelcoords

Andrews plot Biplot Glyph plot

Parallel coordinates plot

Cluster Plots

9

dendrogram manovacluster silhouette

Dendrogram plot

Dendrogram of group mean clusters following MANOVA Silhouette plot

Classification Plots

perfcurve

Compute Receiver Operating Characteristic (ROC) curve or other performance curve for classifier output Plot tree

view

(classregtree)

DOE Plots

interactionplot maineffectsplot multivarichart rsmdemo rstool

Interaction plot for grouped data Main effects plot for grouped data Multivari chart for grouped data

Interactive response surface demonstration Interactive response surface modeling

SPC Plots

capaplot controlchart histfit normspec

Process capability plot Shewhart control charts Histogram with normal fit

Normal density plot between specifications

Probability Distributions

Distribution Objects Distribution Plots Probability Density Cumulative Distribution Inverse Cumulative Distribution Distribution Statistics 10

Distribution Fitting Negative Log-Likelihood Random Number Generators Quasi-Random Numbers Piecewise Distributions Distribution Objects

cdf (ProbDist)

Return cumulative distribution function (CDF) for ProbDist object

fitdist Fit probability distribution to data icdf Return inverse cumulative distribution function (ProbDistUnivKernel) (ICDF) for ProbDistUnivKernel object icdf Return inverse cumulative distribution function (ProbDistUnivParam) (ICDF) for ProbDistUnivParam object iqr Return interquartile range (IQR) for (ProbDistUnivKernel) ProbDistUnivKernel object iqr Return interquartile range (IQR) for (ProbDistUnivParam) ProbDistUnivParam object

mean Return mean of ProbDistUnivParam object (ProbDistUnivParam) median Return median of ProbDistUnivKernel object (ProbDistUnivKernel)

median Return median of ProbDistUnivParam object (ProbDistUnivParam)

paramci Return parameter confidence intervals of (ProbDistUnivParam) ProbDistUnivParam object pdf (ProbDist)

Return probability density function (PDF) for ProbDist object

Construct ProbDistUnivParam object

Generate random number drawn from ProbDist object

ProbDistUnivKernel Construct ProbDistUnivKernel object ProbDistUnivParam random (ProbDist)

std Return standard deviation of ProbDistUnivParam (ProbDistUnivParam) object

var Return variance of ProbDistUnivParam object (ProbDistUnivParam)

Distribution Plots

11

boxplot cdfplot dfittool disttool ecdfhist fsurfht hist3 histfit normplot normspec pareto probplot qqplot randtool scatterhist surfht wblplot

Box plot

Empirical cumulative distribution function plot Interactive distribution fitting

Interactive density and distribution plots

Empirical cumulative distribution function histogram Interactive contour plot Bivariate histogram Histogram with normal fit Normal probability plot

Normal density plot between specifications Pareto chart Probability plots

Quantile-quantile plot

Interactive random number generation Scatter plot with marginal histograms Interactive contour plot Weibull probability plot

Probability Density

betapdf binopdf chi2pdf copulapdf disttool evpdf exppdf fpdf gampdf geopdf gevpdf gppdf hygepdf ksdensity lognpdf mnpdf mvnpdf

Beta probability density function Binomial probability density function Chi-square probability density function Copula probability density function Interactive density and distribution plots Extreme value probability density function Exponential probability density function

F probability density function Gamma probability density function Geometric probability density function Generalized extreme value probability density function

Generalized Pareto probability density function Hypergeometric probability density function Kernel smoothing density estimate Lognormal probability density function Multinomial probability density function Multivariate normal probability density

12

function

mvtpdf nbinpdf ncfpdf nctpdf ncx2pdf normpdf pdf

pdf (gmdistribution)

Multivariate t probability density function Negative binomial probability density function Noncentral F probability density function Noncentral t probability density function Noncentral chi-square probability density function

Normal probability density function Probability density functions

Probability density function for Gaussian mixture distribution

pdf Probability density function for piecewise (piecewisedistribution) distribution poisspdf

Poisson probability density function

random Random numbers from piecewise distribution (piecewisedistribution) raylpdf tpdf unidpdf unifpdf wblpdf

Rayleigh probability density function

Student's t probability density function

Discrete uniform probability density function Continuous uniform probability density function Weibull probability density function

Cumulative Distribution

betacdf binocdf cdf

cdf (gmdistribution)

Beta cumulative distribution function Binomial cumulative distribution function Cumulative distribution functions

Cumulative distribution function for Gaussian mixture distribution

cdf Cumulative distribution function for piecewise (piecewisedistribution) distribution cdfplot chi2cdf copulacdf disttool ecdf ecdfhist evcdf

Empirical cumulative distribution function plot Chi-square cumulative distribution function Copula cumulative distribution function Interactive density and distribution plots Empirical cumulative distribution function Empirical cumulative distribution function

histogram

Extreme value cumulative distribution function

13

expcdf fcdf gamcdf geocdf gevcdf gpcdf hygecdf logncdf mvncdf mvtcdf ncfcdf nctcdf ncx2cdf normcdf poisscdf raylcdf tcdf unidcdf unifcdf wblcdf

Exponential cumulative distribution function

F cumulative distribution function Gamma cumulative distribution function Geometric cumulative distribution function Generalized extreme value cumulative distribution function

Generalized Pareto cumulative distribution function

Hypergeometric cumulative distribution function Lognormal cumulative distribution function Multivariate normal cumulative distribution function

Multivariate t cumulative distribution function Noncentral F cumulative distribution function Noncentral t cumulative distribution function Noncentral chi-square cumulative distribution function

Normal cumulative distribution function Poisson cumulative distribution function Rayleigh cumulative distribution function Student's t cumulative distribution function Discrete uniform cumulative distribution function

Continuous uniform cumulative distribution function

Weibull cumulative distribution function

Inverse Cumulative Distribution

betainv binoinv chi2inv evinv expinv finv

Beta inverse cumulative distribution function Binomial inverse cumulative distribution function

Chi-square inverse cumulative distribution function

Extreme value inverse cumulative distribution function

Exponential inverse cumulative distribution function

F inverse cumulative distribution function

14

gaminv geoinv gevinv gpinv hygeinv icdf

Gamma inverse cumulative distribution function Geometric inverse cumulative distribution function

Generalized extreme value inverse cumulative distribution function

Generalized Pareto inverse cumulative distribution function

Hypergeometric inverse cumulative distribution function

Inverse cumulative distribution functions

icdf Inverse cumulative distribution function for (piecewisedistribution) piecewise distribution logninv nbininv ncfinv nctinv ncx2inv norminv poissinv raylinv tinv unidinv unifinv wblinv

Lognormal inverse cumulative distribution

function

Negative binomial inverse cumulative distribution function

Noncentral F inverse cumulative distribution function

Noncentral t inverse cumulative distribution function

Noncentral chi-square inverse cumulative distribution function

Normal inverse cumulative distribution function Poisson inverse cumulative distribution function

Rayleigh inverse cumulative distribution function

Student's t inverse cumulative distribution function

Discrete uniform inverse cumulative distribution function

Continuous uniform inverse cumulative distribution function

Weibull inverse cumulative distribution function

Distribution Statistics

betastat binostat

Beta mean and variance Binomial mean and variance

15

chi2stat copulastat evstat expstat fstat gamstat geostat gevstat gpstat hygestat lognstat nbinstat ncfstat nctstat ncx2stat normstat poisstat raylstat tstat unidstat unifstat wblstat

Chi-square mean and variance Copula rank correlation

Extreme value mean and variance Exponential mean and variance

F mean and variance Gamma mean and variance Geometric mean and variance

Generalized extreme value mean and variance Generalized Pareto mean and variance Hypergeometric mean and variance Lognormal mean and variance

Negative binomial mean and variance Noncentral F mean and variance Noncentral t mean and variance

Noncentral chi-square mean and variance Normal mean and variance Poisson mean and variance Rayleigh mean and variance Student's t mean and variance Discrete uniform mean and variance Continuous uniform mean and variance Weibull mean and variance

Distribution Fitting

Supported Distributions Piecewise Distributions Supported Distributions betafit binofit copulafit copulaparam dfittool evfit expfit

Beta parameter estimates Binomial parameter estimates Fit copula to data

Copula parameters as function of rank correlation Interactive distribution fitting Extreme value parameter estimates Exponential parameter estimates

16

fit Gaussian mixture parameter estimates (gmdistribution) gamfit gevfit gpfit histfit johnsrnd lognfit mle mlecov nbinfit normfit normplot pearsrnd poissfit raylfit unifit wblfit wblplot

Gamma parameter estimates

Generalized extreme value parameter estimates Generalized Pareto parameter estimates Histogram with normal fit Johnson system random numbers Lognormal parameter estimates Maximum likelihood estimates

Asymptotic covariance of maximum likelihood estimators

Negative binomial parameter estimates Normal parameter estimates Normal probability plot Pearson system random numbers Poisson parameter estimates Rayleigh parameter estimates

Continuous uniform parameter estimates Weibull parameter estimates Weibull probability plot

Piecewise Distributions

boundary Piecewise distribution boundaries (piecewisedistribution) lowerparams (paretotails)

Lower Pareto tails parameters

nsegments Number of segments (piecewisedistribution) paretotails

Construct Pareto tails object

piecewisedistribution Create piecewise distribution object segment Segments containing values (piecewisedistribution) upperparams (paretotails)

Upper Pareto tails parameters

Negative Log-Likelihood

betalike evlike

Beta negative log-likelihood

Extreme value negative log-likelihood

17

explike gamlike gevlike gplike lognlike mvregresslike normlike wbllike

Exponential negative log-likelihood Gamma negative log-likelihood

Generalized extreme value negative log-likelihood Generalized Pareto negative log-likelihood Lognormal negative log-likelihood

Negative log-likelihood for multivariate regression Normal negative log-likelihood Weibull negative log-likelihood

Random Number Generators

betarnd binornd chi2rnd copularnd datasample evrnd exprnd frnd gamrnd geornd gevrnd gprnd hygernd iwishrnd johnsrnd lhsdesign lhsnorm lognrnd mhsample mnrnd mvnrnd mvtrnd nbinrnd ncfrnd nctrnd ncx2rnd

Beta random numbers Binomial random numbers Chi-square random numbers Copula random numbers

Randomly sample from data, with or without replacement

Extreme value random numbers Exponential random numbers

F random numbers Gamma random numbers Geometric random numbers

Generalized extreme value random numbers Generalized Pareto random numbers Hypergeometric random numbers Inverse Wishart random numbers Johnson system random numbers Latin hypercube sample

Latin hypercube sample from normal distribution Lognormal random numbers Metropolis-Hastings sample Multinomial random numbers

Multivariate normal random numbers Multivariate t random numbers Negative binomial random numbers Noncentral F random numbers Noncentral t random numbers

Noncentral chi-square random numbers

18

normrnd pearsrnd poissrnd randg random

Normal random numbers

Pearson system random numbers Poisson random numbers Gamma random numbers Random numbers

random (gmdistribution) Random numbers from Gaussian mixture

distribution random Random numbers from piecewise distribution (piecewisedistribution) randsample randtool raylrnd slicesample trnd unidrnd unifrnd wblrnd wishrnd

Random sample

Interactive random number generation Rayleigh random numbers Slice sampler

Student's t random numbers Discrete uniform random numbers Continuous uniform random numbers Weibull random numbers Wishart random numbers

Quasi-Random Numbers

addlistener (qrandstream) delete

(qrandstream) end (qrandset) findobj

(qrandstream) findprop

(qrandstream)

Add listener for event Delete handle object

Last index in indexing expression for point set Find objects matching specified conditions Find property of MATLAB handle object

eq (qrandstream) Test handle equality

ge (qrandstream) Greater than or equal relation for handles gt (qrandstream) Greater than relation for handles haltonset isvalid

(qrandstream)

Construct Halton quasi-random point set Test handle validity

le (qrandstream) Less than or equal relation for handles length (qrandset) Length of point set

lt (qrandstream) Less than relation for handles

19

ndims (qrandset) Number of dimensions in matrix ne (qrandstream) Not equal relation for handles net (qrandset) notify

(qrandstream) qrand

(qrandstream) qrandset qrandstream reset

(qrandstream) scramble (qrandset) size (qrandset) sobolset

Generate quasi-random point set Notify listeners of event

Generate quasi-random points from stream Abstract quasi-random point set class Construct quasi-random number stream Reset state

Scramble quasi-random point set Number of dimensions in matrix

Construct Sobol quasi-random point set

rand (qrandstream) Generate quasi-random points from stream

Piecewise Distributions

boundary Piecewise distribution boundaries (piecewisedistribution) cdf Cumulative distribution function for piecewise (piecewisedistribution) distribution icdf Inverse cumulative distribution function for (piecewisedistribution) piecewise distribution lowerparams (paretotails)

Lower Pareto tails parameters

nsegments Number of segments (piecewisedistribution) paretotails

Construct Pareto tails object

pdf Probability density function for piecewise (piecewisedistribution) distribution piecewisedistribution Create piecewise distribution object random Random numbers from piecewise distribution (piecewisedistribution)

segment Segments containing values (piecewisedistribution) upperparams (paretotails)

Upper Pareto tails parameters

20

Hypothesis Tests

ansaribradley barttest canoncorr chi2gof dwtest friedman jbtest kruskalwallis kstest kstest2 lillietest linhyptest ranksum runstest sampsizepwr signrank signtest ttest ttest2 vartest vartest2 vartestn zscore ztest

Ansari-Bradley test Bartlett's test Canonical correlation

Chi-square goodness-of-fit test Durbin-Watson test Friedman's test Jarque-Bera test Kruskal-Wallis test

One-sample Kolmogorov-Smirnov test Two-sample Kolmogorov-Smirnov test Lilliefors test Linear hypothesis test Wilcoxon rank sum test Run test for randomness Sample size and power of test Wilcoxon signed rank test Sign test

One-sample and paired-sample t-test Two-sample t-test Chi-square variance test

Two-sample F-test for equal variances

Bartlett multiple-sample test for equal variances Standardized z-scores

z-test

Analysis of Variance

ANOVA Plots ANOVA Operations ANOVA Plots

anova1 aoctool

One-way analysis of variance Interactive analysis of covariance

21

manovacluster multcompare

Dendrogram of group mean clusters following MANOVA Multiple comparison test

ANOVA Operations

anova1 anova2 anovan aoctool dummyvar friedman kruskalwallis manova1 manovacluster multcompare

One-way analysis of variance Two-way analysis of variance

N-way analysis of variance

Interactive analysis of covariance Create dummy variables Friedman's test Kruskal-Wallis test

One-way multivariate analysis of variance

Dendrogram of group mean clusters following MANOVA Multiple comparison test

Parametric Regression Analysis

Regression Plots Linear Regression Nonlinear Regression Regression Plots

addedvarplot gline

lassoPlot lsline polytool rcoplot refcurve refline robustdemo rsmdemo rstool view

Added-variable plot

Interactively add line to plot Trace plot of lasso fit

Add least-squares line to scatter plot Interactive polynomial fitting Residual case order plot Add reference curve to plot Add reference line to plot Interactive robust regression

Interactive response surface demonstration Interactive response surface modeling Plot tree

22

(classregtree)

Linear Regression

coxphfit dummyvar glmfit glmval invpred lasso leverage mnrfit mnrval mvregress mvregresslike plsregress polyconf polytool regress regstats ridge robustdemo robustfit rsmdemo rstool stepwise stepwisefit x2fx

Cox proportional hazards regression Create dummy variables

Generalized linear model regression Generalized linear model values Inverse prediction

Regularized least-squares regression using lasso or elastic net algorithms Leverage

Multinomial logistic regression Multinomial logistic regression values Multivariate linear regression

Negative log-likelihood for multivariate regression Partial least-squares regression Polynomial confidence intervals Interactive polynomial fitting Multiple linear regression Regression diagnostics Ridge regression

Interactive robust regression Robust regression

Interactive response surface demonstration Interactive response surface modeling Interactive stepwise regression Stepwise regression

Convert predictor matrix to design matrix

Back to Top of Section

Nonlinear Regression

dummyvar hougen nlinfit

Create dummy variables Hougen-Watson model Nonlinear regression

23

nlintool nlmefit nlmefitsa nlparci nlpredci

Interactive nonlinear regression Nonlinear mixed-effects estimation

Fit nonlinear mixed effects model with stochastic EM algorithm

Nonlinear regression parameter confidence intervals Nonlinear regression prediction confidence intervals

Back to Top

Multivariate Methods

Multivariate Plots Multidimensional Scaling Procrustes Analysis Feature Selection Feature Transformation Multivariate Plots

andrewsplot biplot glyphplot parallelcoords

Andrews plot Biplot Glyph plot

Parallel coordinates plot

Multidimensional Scaling

cmdscale mahal mdscale pdist squareform

Classical multidimensional scaling Mahalanobis distance

Nonclassical multidimensional scaling Pairwise distance between pairs of objects Format distance matrix

Procrustes Analysis

procrustes

Procrustes analysis

24

Feature Selection

sequentialfs

Sequential feature selection

Feature Transformation

Nonnegative Matrix Factorization Principal Component Analysis Factor Analysis Nonnegative Matrix Factorization nnmf

Nonnegative matrix factorization

Principal Component Analysis barttest pareto pcacov pcares princomp Factor Analysis factoran

Factor analysis Bartlett's test Pareto chart

Principal component analysis on covariance matrix Residuals from principal component analysis Principal component analysis (PCA) on data

Cluster Analysis

Cluster Plots Hierarchical Clustering K-Means Clustering Gaussian Mixture Models Cluster Plots

dendrogram

Dendrogram plot

25

manovacluster silhouette

Dendrogram of group mean clusters following MANOVA Silhouette plot

Hierarchical Clustering

cluster clusterdata cophenet inconsistent linkage pdist squareform

Construct agglomerative clusters from linkages Agglomerative clusters from data Cophenetic correlation coefficient Inconsistency coefficient

Agglomerative hierarchical cluster tree Pairwise distance between pairs of objects Format distance matrix

K-Means Clustering

kmeans mahal

K-means clustering Mahalanobis distance

Gaussian Mixture Models

cdf Cumulative distribution function for Gaussian (gmdistribution) mixture distribution

cluster Construct clusters from Gaussian mixture (gmdistribution) distribution

fit Gaussian mixture parameter estimates (gmdistribution) gmdistribution

Construct Gaussian mixture distribution

mahal Mahalanobis distance to component means (gmdistribution)

pdf Probability density function for Gaussian mixture (gmdistribution) distribution

posterior Posterior probabilities of components (gmdistribution)

random Random numbers from Gaussian mixture distribution (gmdistribution)

Model Assessment

26

confusionmat crossval cvpartition repartition (cvpartition) training

(cvpartition)

Confusion matrix

Loss estimate using cross-validation Create cross-validation partition for data Repartition data for cross-validation

test (cvpartition) Test indices for cross-validation

Training indices for cross-validation

Parametric Classification

Discriminant Analysis Naive Bayes Classification Classification Plots Discriminant Analysis

ClassificationDiscriminant ClassificationPartitionedModel classify

Discriminant analysis classification

Cross-validated classification model

Discriminant analysis

compact Compact discriminant analysis (ClassificationDiscriminant) classifier

CompactClassificationDiscriminant Compact discriminant analysis class crossval

(ClassificationDiscriminant)

Cross-validated discriminant analysis classifier

edge Classification edge (CompactClassificationDiscriminant)

fit (ClassificationDiscriminant) Fit discriminant analysis

classifier kfoldEdge

(ClassificationPartitionedModel) kfoldfun

(ClassificationPartitionedModel) kfoldLoss

(ClassificationPartitionedModel) kfoldMargin

Classification edge for

observations not used for training Cross validate function

Classification loss for

observations not used for training Classification margins for

27

(ClassificationPartitionedModel) kfoldPredict

(ClassificationPartitionedModel)

observations not used for training Predict response for observations not used for training

loss Classification error (CompactClassificationDiscriminant)

mahal Mahalanobis distance to class means (CompactClassificationDiscriminant)

make (ClassificationDiscriminant) Construct discriminant analysis

classifier from parameters margin Classification margins (CompactClassificationDiscriminant)

predict Predict classification (CompactClassificationDiscriminant) resubEdge

(ClassificationDiscriminant) resubLoss

(ClassificationDiscriminant) resubMargin

(ClassificationDiscriminant) resubPredict

(ClassificationDiscriminant)

Classification edge by resubstitution

Classification error by resubstitution

Classification margins by resubstitution

Predict resubstitution response of classifier

Naive Bayes Classification

fit (NaiveBayes) Create Naive Bayes classifier object by fitting

training data NaiveBayes posterior (NaiveBayes) predict

(NaiveBayes)

Create NaiveBayes object

Compute posterior probability of each class for test data

Predict class label for test data

Classification Plots

perfcurve

Compute Receiver Operating Characteristic (ROC) curve or other performance curve for classifier output Plot tree

view

(classregtree)

28

Nonparametric Supervised Learning

Distance Computation and Nearest Neighbor Search

createns knnsearch

Create object to use in k-nearest neighbors search Find k-nearest neighbors using data

knnsearch Find k-nearest neighbors using ExhaustiveSearcher (ExhaustiveSearcher) object knnsearch

(KDTreeSearcher) pdist pdist2 rangesearch

Find k-nearest neighbors using KDTreeSearcher object

Pairwise distance between pairs of objects Pairwise distance between two sets of observations Find all neighbors within specified distance

rangesearch Find all neighbors within specified distance using (ExhaustiveSearcher) ExhaustiveSearcher object rangesearch

(KDTreeSearcher) relieff

Find all neighbors within specified distance using KDTreeSearcher object

Importance of attributes (predictors) using ReliefF algorithm

Classification Trees

catsplit (classregtree) children (classregtree) classcount (classregtree) ClassificationTree classname (classregtree) classprob (classregtree) classregtree classregtree

compact (ClassificationTree) CompactClassificationTree crossval (ClassificationTree)

Categorical splits used for branches in decision tree Child nodes Class counts

Binary decision tree for classification

Class names for classification decision tree Class probabilities

Classification and regression trees Construct classification and regression trees Compact tree

Compact classification tree Cross-validated decision tree

29

ClassificationPartitionedModel Cross-validated classification model

cutcategories (classregtree) cutpoint (classregtree) cuttype (classregtree) cutvar (classregtree) cvloss (ClassificationTree)

Cut categories

Decision tree cut point values Cut types

Cut variable names

Classification error by cross validation

Predicted responses Fit classification tree Test node for branch

edge (CompactClassificationTree) Classification edge eval (classregtree) fit (ClassificationTree) isbranch (classregtree)

kfoldEdge Classification edge for observations (ClassificationPartitionedModel) not used for training kfoldfun Cross validate function (ClassificationPartitionedModel)

kfoldLoss Classification loss for observations (ClassificationPartitionedModel) not used for training kfoldMargin Classification margins for (ClassificationPartitionedModel) observations not used for training kfoldPredict Predict response for observations not (ClassificationPartitionedModel) used for training loss (CompactClassificationTree) Classification error

margin Classification margins (CompactClassificationTree)

meansurrvarassoc (classregtree) Mean predictive measure of association

for surrogate splits in decision tree meanSurrVarAssoc

(CompactClassificationTree) nodeclass (classregtree) nodeerr (classregtree) nodeprob (classregtree) nodesize (classregtree) numnodes (classregtree) parent (classregtree) predict

(CompactClassificationTree) predictorImportance

(CompactClassificationTree) prune (ClassificationTree) prune (classregtree)

Mean predictive measure of association for surrogate splits in decision tree Class values of nodes of classification tree

Return vector of node errors Node probabilities Return node size Number of nodes Parent node

Predict classification

Estimates of predictor importance Produce sequence of subtrees by pruning Prune tree

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growTrees (TreeBagger) kfoldfun

(RegressionPartitionedModel)

Train additional trees and add to ensemble

Cross validate function

kfoldLoss Cross-validation loss of partitioned (RegressionPartitionedEnsemble) regression ensemble kfoldPredict

(RegressionPartitionedModel) loss

(CompactRegressionEnsemble) mdsProx (CompactTreeBagger) mdsProx (TreeBagger)

Predict response for observations not used for training. Regression error

Multidimensional scaling of proximity matrix

Multidimensional scaling of proximity matrix

Out-of-bag error

Out-of-bag regression error

Predict out-of-bag response of ensemble Ensemble predictions for out-of-bag observations

Outlier measure for data Predict response of ensemble Predict response Predict response

Estimates of predictor importance

meanMargin (CompactTreeBagger) Mean classification margin oobError (TreeBagger) oobLoss

(RegressionBaggedEnsemble) oobPredict

(RegressionBaggedEnsemble) oobPredict (TreeBagger) outlierMeasure

(CompactTreeBagger)

predict

(CompactRegressionEnsemble) predict (CompactTreeBagger) predict (TreeBagger) predictorImportance

(CompactRegressionEnsemble) RegressionBaggedEnsemble

proximity (CompactTreeBagger) Proximity matrix for data

Regression ensemble grown by resampling

RegressionEnsemble Ensemble regression

RegressionPartitionedEnsemble Cross-validated regression ensemble regularize (RegressionEnsemble) Find weights to minimize resubstitution

error plus penalty term resubLoss (RegressionEnsemble) Regression error by resubstitution resubPredict

(RegressionEnsemble) resume (RegressionEnsemble)

Predict response of ensemble by resubstitution

Resume training ensemble

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resume Resume training ensemble (RegressionPartitionedEnsemble) SetDefaultYfit

(CompactTreeBagger)

shrink (RegressionEnsemble) TreeBagger

Set default value for predict Prune ensemble

Bootstrap aggregation for ensemble of decision trees

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Hidden Markov Models

hmmdecode hmmestimate hmmgenerate hmmtrain hmmviterbi

Hidden Markov model posterior state probabilities Hidden Markov model parameter estimates from emissions and states

Hidden Markov model states and emissions Hidden Markov model parameter estimates from emissions

Hidden Markov model most probable state path

Design of Experiments

DOE Plots Full Factorial Designs Fractional Factorial Designs Response Surface Designs D-Optimal Designs Latin Hypercube Designs Quasi-Random Designs DOE Plots

interactionplot maineffectsplot multivarichart

Interaction plot for grouped data Main effects plot for grouped data Multivari chart for grouped data

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rsmdemo rstool

Interactive response surface demonstration Interactive response surface modeling

Full Factorial Designs

ff2n fullfact

Two-level full factorial design Full factorial design

Fractional Factorial Designs

fracfact fracfactgen

Fractional factorial design

Fractional factorial design generators

Response Surface Designs

bbdesign ccdesign

Box-Behnken design Central composite design

D-Optimal Designs

candexch candgen cordexch daugment dcovary rowexch rsmdemo

D-optimal design from candidate set using row exchanges

Candidate set generation Coordinate exchange

D-optimal augmentation

D-optimal design with fixed covariates Row exchange

Interactive response surface demonstration

Latin Hypercube Designs

lhsdesign lhsnorm

Latin hypercube sample

Latin hypercube sample from normal distribution

Quasi-Random Designs

addlistener

Add listener for event

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(qrandstream) delete

(qrandstream) end (qrandset) findobj

(qrandstream) findprop

(qrandstream)

Delete handle object

Last index in indexing expression for point set Find objects matching specified conditions Find property of MATLAB handle object

eq (qrandstream) Test handle equality

ge (qrandstream) Greater than or equal relation for handles gt (qrandstream) Greater than relation for handles haltonset isvalid

(qrandstream)

Construct Halton quasi-random point set Test handle validity

le (qrandstream) Less than or equal relation for handles length (qrandset) Length of point set

lt (qrandstream) Less than relation for handles ndims (qrandset) Number of dimensions in matrix ne (qrandstream) Not equal relation for handles net (qrandset) notify

(qrandstream) qrand

(qrandstream) qrandset qrandstream reset

(qrandstream) scramble (qrandset) size (qrandset) sobolset

Generate quasi-random point set Notify listeners of event

Generate quasi-random points from stream Abstract quasi-random point set class Construct quasi-random number stream Reset state

Scramble quasi-random point set Number of dimensions in matrix

Construct Sobol quasi-random point set

rand (qrandstream) Generate quasi-random points from stream

Statistical Process Control

SPC Plots SPC Functions 39

SPC Plots

capaplot controlchart histfit normspec

SPC Functions

capability controlrules gagerr

GUIs

aoctool dfittool disttool fsurfht polytool randtool regstats robustdemo rsmdemo rstool surfht

Utilities

combnk perms statget statset zscore

Process capability plot Shewhart control charts Histogram with normal fit

Normal density plot between specifications

Process capability indices

Western Electric and Nelson control rules Gage repeatability and reproducibility study

Interactive analysis of covariance

Interactive distribution fitting

Interactive density and distribution plots Interactive contour plot Interactive polynomial fitting Interactive random number generation Regression diagnostics Interactive robust regression

Interactive response surface demonstration Interactive response surface modeling Interactive contour plot

Enumeration of combinations Enumeration of permutations

Access values in statistics options structure Create statistics options structure Standardized z-scores

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