Download All

No BSD License

Highlights from
linstats 2006b

How to build a linear model
Model Validation Tutorial
hypothesis testing tutorial
inner product spaces and orth...
mmvn_tutorial
anova( glm, tests, reference ... ANOVA n-way analysis of variance and analysis of covariance
anova_compare( x, y ) ANOVA_COMPARE internal callback to compare stats structures
anova_table(a, i, source_name... ANOVA_TABLE builds a standard anova table
array2vec( y, varargin ) ARRAY2VEC converts an ndim table headers into column vectors
boxcox(x,y,noecho, noplot) BOX/COX BoxCox procedure to evaluate the best transformation of the input
breusch_pagan( glm ) BREUSCH_PAGAN constant variance tests for categorical models
brown_forysthe( glm ) BROWN_FORYSTHE constant variance test for continuous x.
center(X, V, dim) CENTER subtracts a vector from each row of a matrix
chist( f, horiz ) CHIST categorical histogram
ciplot( x, y, ci, color_group... CIPLOT confidence interval plot with multiple factor grouping
clegend( h, labels, varargin ... CLEGEND create legend based on face color
coeff2eqn( coeffs, var_names,... COEFF2EQN text representation of a set of equations
colorfulcube( M, creq, method... COLORFULCUBE produces useful colormaps
confidence_intervals( se, dfe... CONFIDENCE_INTERVALS confidence interval for multiple-test correction
constrain( c ) CONSTRAIN orthogonal basis for the null space c
crosstab2( varargin ) CROSSTAB2 cross tabulation with labels
cvplot( m, term, varargin ) CVPLOT plots the canonical variables from a multivariate analysis
decode( glm, terms ) DECODE decodes a model into index dummy variables
deg2rad(deg) DEG2RAD convers degrees to radians
dvplot( glm, tests, reference... DVPPLOT dropped variable plot
ellipse( M, V, dims, sd ) ELLIPSE draws 2d and 3d ellipse(s)
encode( y, var_type, model, v... ENCODE encode a linear model
encode_vars( ivar, var_type, ... ENCODE_VARS helper function for encode
estimates_table(a, response, ... ESTIMATES_TABLE format parameter estimates into a table
export( fn, tbl, nfmt, sfmt ... EXPORT exports the data from a cell_array to the given file
export_table( fn, col_names, ... EXPORT_TABLE writes a cell table to file
fan_table(Loadings, varnames)... FAN_TABLE factor analysis table
fdr_calc( p ) FDR_CALC helper function to calculate the false discovery rate from a set
fdr_plot( p ) FDR_PLOT false discovery rate plote.
fexact( a, b, c, d ) FEXACT fishers exact test
ffact( q ) FFACT full facorial design
findMode( X, varargin ) FINDMODE estimated mode from a sample
foldChange( x, base ) FOLDCHANGE - converts log(ratio) into fold change
gamplot( ch, phat ) GAMPLOT overlay a gamma distribution on a a histogram of ch.
getAxisInset( xp, yp ) GETAXISINSET return coordinates for relative positions
getColExtent( tbl ) GETCOLEXTENT gets the width and height of cells in a table
getcontrasts( p, method ) GETCONTRASTS returns a set of common constrasts. helper for lsconstrasts
gettests( glm, sstype ) GETTESTS help function to return test matrices used by anova
ghist( x, grpi, bins ) GHIST histogram for grouped data
gmean( y, groups) GMEAN - efficiently calculate group means
grp2ind( varargin ) GRP2IND converts grouping variables in integer indices
head( data, rows, cols ) HEAD the first rows and columns of data
histinv( x, fx, n ) HISTINV
impute( y, glm ) IMPUTE imputes missing values using least-squares predictions
imputeMissingRows( mat ) IMPUTEMISSINGROWS
ind2grp( gi, varargin ) IND2GRP recreates factors from dummy variables and labels
ind2logical( i, d ) IND2LOGICAL converts integer index into logical of size d
ind2subl( m, k ) IND2SUBL converts linear indices from upper triangle to square form
indexof( v, d ) INDEXOF indices of set members
iplot( glm, terms, response ) IPLOT interaction plot
isdiscrete( x ) ISDISCRETE heuristic test of whether x is discrete
isnested( g1, g2 ) ISNESTED tests whether two factors are nested
issingular( A, cmat ) ISSINGULAR returns singularity information about system of equations
jitter( x, range ) JITTER adds jitter (uniform noise) to the values in x.
jplot_table(col_names, vararg... JPLOT_TABLE plot a table to a figure window
leverage_plot( glm, varargin ... LEVERAGE_PLOT
lindc( A, tol ) LINDC returns the linear dependent columns of A
linspace(d1, d2, n) linspace Logarithmically spaced vector.
lmodel(nterms,order) LMODEL returns common linear design matrices
lof( glm ) LOF lack of fit statistics
logspace(d1, d2, n) LOGSPACE Logarithmically spaced vector.
lscontrast( glm, term, L, alp... LSCONTRAST contrast means and statistics
lsestimates( glm, term, respo... LSESTIMATES - least squares estimates for model parameters
mah( y, u, v ) MAH mahalonbis distance from a set of points to population centroids
manova( glm ) MANOVA multivariate analysis of variance
manova_table( stats, term ) MANOVA_TABLE output results from a manova
mat2vec( A ) MAT2VEC converts matrix of numbers to a list of numeric cell arrays
mat_compare( x, y, tol ) function, comare two matrices to see
mdensity_plot( x ) MDENSITY_PLOT
mdummy(x, method) MDUMMY enodes integer index (grouping) variables into a design matrix
mdummyx(x) MDUMMYX encode a design matrix for each unique crossed terms
mgrpcov( x, g ) MGRPCOV grouped means and covariances
mgrpstats( x, g ) MGRPSTATS univariate summary statistics stratified by group
mineffect( stats ) MINEFFECT finds the smallest estimated change in an estimate
mlegend( h, labels, varargin ... MLEGEND create legend based on marker
mmvn_R2V( R ) MMVN_R2V convert chol decomposed variances from a vector to variance matrix
mmvn_cdf(X, M, V, W ) Mixture of multivariate nomral probabilities
mmvn_expectation(X, varargin) MMVN_EXPECTATION mixture multivariate expectation
mmvn_fit(X, k, Init, options ... MMVN_FIT fits a mixture of gaussians.
mmvn_fit_movie( X, Opt, L, ol... MMVN_FIT_MOVIE callback function for mmvn_fit.
mmvn_gen(m,varargin ) MMVN_GEN generates a mixture of multivariate guassians
mmvn_getTheta( varargin ) MMVN_GETTHETA creates structure theta from various inputs
mmvn_likelihood(X,varargin) MMVN_LIKELIHOOD Calculates the log(likelihood ) of a mixture of mutlivariate gaussians
mmvn_logl_surface(X, theta, k... MMVN_LOGL_SURFACE a 2d contour of the log likelihood surface
mmvn_maximization(X, E, h0, b... MMVN_MAXIMIZATION the second step of the EM algorithm
mmvn_pdf(X, varargin) MMVN_PDF Mixture of multivariate nomal probabilities
model2eqn( model, coeff_names... MODEL2EQN creates a text representation of a model
mscatter( x, y, color_groupin... MSCATTER scatter plot of x versus y grouped by up to 3 factors
mstats( glm, y, cmat ) MSTATS least squares solution and statistics for linear model
nanzscore( d, reference ) NANZSCORE zscore for data with missing values
ndscatter( A, labels, dims, p... NDSCATTER flexible interactive plot for viewing n-dimensional data
num2ord(x) NUM2ORD Convert numbers to an ordinal string.
numreps( Y ) NUMREPS returns a unique replicate number for an observation
paired_resid_plot(a,b,c) PAIRED_RESID_PLOT - plots a-b versus avg(a,b)
paste( A, i, B ) PASTE paste columns into a matrix
pcplot( scores, latent, varar... PCPLOT plots principal components colored by explanatory factors
plot_table(col_names, varargi... PLOT_TABLE plot a table to a figure window
rad2deg(r) RAD2DEG radians to degrees
range(x,dim) RANGE drop in replacement for matlab's range.
reflines(glm, x1, f1) REFLINES plots a series of reference lines for an ANACOVA model
regexpfind( str, pat ) REGEXPFIND use regular expression to find patters
resid_plot( stats, varargin) RESID_PLOT plot of predicted response versus residuals.
roc_calc( real, test_value, l... ROC_CALC calculations for reciever operating characteristic curve
roc_compare( auc, se ) ROC_COMPARE compares the area under multiple AUCs
roc_pdf( real, test_value, bi... ROC_PDF separate density plots for true and false positive samples
roc_plot( real, test_value, c... ROC_PLOT reciever operating characteristic curve
rotate2d( A, theta ) ROTATE2D rotates a 2d data matrix
scale(X, V, dim) SCALE divides a vector from each row in a matrix
scaledhist( a, bins ) SCALEDHIST histogram with the total area equal 1
scree( latent, alpha ) SCREE scree plot
shuffle( d ) SHUFFLE randomize rows of a matrix
slegend( h, labels, varargin ... SLEGEND create legend based on marker size
solve( A, y, cmat ) SOLVE solve an optionally constrained linear model
sov_plot( a ) SOV_PLOT a bar plot of sources of variability
srepmat( form, a, siz ) SREPMAT replicate standard matrices
sresid( ls ) SRESID cacluates studentized residuals
sresid_plot( stats, varargin) SRESID_PLOT studentized residual plot
stats_compare( x, y ) STATS_COMPARE internal callback to compare stats structures
stdrcdf(q, v, r, upper) STRCDF calls matlab's stdrcdf function
stdrinv(p, v, r) STDRINV
str2numnan( str ) STR2NUMNAN converts a str of cellstr into numbers
subtract_effect( glm, terms ) SUBTRACT_EFFECT subtracts the effect from the response
summary( y ) SUMMARY statistical summary table of values in y
svd_filter( d, c ) SVD_FILTER demonstrate svd to removie noise and compress data
swap(a,b) SWAP swaps the values of two variables
table( col_names, varargin ) TABLE create a cell table
tail( data, rows, cols ) TAIL show the last rows of a matrix
tests2eqn( glm, tests, refere... TESTS2EQN produces names for anova tests (helper for anova)
tri2sqind( m, k ) TRI2SQIND subscript and linear indices for upper tri portion of matrix
variance_plot( stats ) VARIANCE_PLOT plot to show reveal variance abnormalities
vec2array( y, varargin ) VEC2ARRAY converts a vector to n-dim array
volcano( logratio, pval ) VOLCANO a volcano plot of probabilities and effect size
whist(Y,x,w) WHIST weighted histogram
MMGate( varargin ) MMGate - extracts rows of x that meet gating criteria
MMView( varargin ) MMView - stores a particular 2d view on md data including cell
MModel( x, s, t, knames) MModel MModel class constructor
TreeSet( varargin ) TreeSet collection of unique nodes arranged in parent child location
Contents.m
canoncorr_tutorial.m
data_sources.m
factoryDefaults.m
jplot_table_test.m
readme.m
readme.m
test_1way.m
test_2way.m
test_3way.m
test_aoc.m
test_custom.m
test_encode.m
test_estimates.m
test_manova.m
test_singularity.m
test_tests.m
test_vtable.m
trace_tutorial.m
unit_tests.m
vtest_plots.m
Disclaimer
View all files

5.0

5.0 | 3 ratings Rate this file 19 Downloads (last 30 days) File Size: 1.66 MB File ID: #13493

linstats 2006b

by Michael Boedigheimer

27 Dec 2006 (Updated 27 Dec 2006)

linear multivariate statistics

| Watch this File

File Information
Description	Second release of Linstats, a toolbox for building, testing and making statistical inferences from linear models. There are many features in this toolbox that are not available in the matlab statistical toolbox including n-way ANACOVA and n-way MANOVA as well numerous diagnostic plots. There is also support for multiple responses and linstats efficiently supports fiting models with up to 100s of thousands of responses. All the features share a unified model building approach. This release includes support for interactive mixture modeling: generate and view multidimensional mixture data, build mixture models and fit models using expectation maximization.
Required Products	Statistics Toolbox
MATLAB release	MATLAB 7.3 (R2006b)

Tags for This File
Everyone's Tags	em anova manova anacova manacova regression tutorial mixture gua, probability, statistics
Tags I've Applied
Add New Tags	Please login to tag files.

Comments and Ratings (4)
11 Jun 2008	Robson Costa
17 Oct 2008	Srinivas Rachakonda
01 May 2010	Pierce	Excellent, i know wrote you this package a while ago. I'm justiwondering if you have any more updates to the package that include a maximum likehood solver
22 Mar 2012	Chris McGraw	Just to be certain, I wanted to ask. I can't determine whether the ENCODE function can specify a non-Normal "link" for the glm -- it looks like it assumes Normal distribution for the error term.

Please login to add a comment or rating.

Tag Activity for this File
Tag	Applied By	Date/Time
statistics	Michael Boedigheimer	22 Oct 2008 08:54:11
probability	Michael Boedigheimer	22 Oct 2008 08:54:11
em anova manova anacova manacova regression tutorial mixture gua	Michael Boedigheimer	22 Oct 2008 08:54:11

Highlights from linstats 2006b

linstats 2006b

Highlights from
linstats 2006b