Restricted Cubic Spline by Leonidas Bantis

Fits the so called restricted cubic spline via least squares and obtains 95% bootstrap based CIs. (spline, restricted cubic spli..., least squares)

[bhat f sse knots CI]=rcspline(x,y,knots,bootsams,atwhich,p...

[bhat ff sse X]=rcs(x,y,knots,plots)

example.m

Nadaraya-Watson smoothing by Jan Motl

A non-parametrical regression (smoothing) tool using Gaussian kernel. (regression, smoothing, smooth)

[smoothed score h]=smoothing(ydata,varargin)

x2fx_names - compound predictor names for x2fx by Dmitry Kaplan

returns NAMES of columns for the output of x2fx() (x2fx, statistics, predictors)

res=x2fx_names(PredictorNames,model)

linfitregsel - term selection in linear regression by Bill Whiten

Select terms in linear regression (equation fitting) using eigenvectors and term significance (regression, term selection, regularised regressio...)

[x,cov,info]=linfitregsel(A,b,optn)

opts=optndfts(args,varargin)

linfitregseldemo.m

Hot to run WEKA classifiers within MATLAB by Gustavo

This is an example on how to select and pass parameters to Weka from MATLAB (weka, machine learning, classification)

RunWekaFromMATLAB.m

Active geometric shape models by Quan Wang

The active geometric shape model is a novel approach for fitting a geometric shape in images. (shape model, image processing, optimization)

BoundMirrorEnsure(A)

BoundMirrorExpand(A)

BoundMirrorShrink(A)

mvsregress by Robert Piche

Robust multivariate regression using the Student-t distribution (statistics, student, studentt)

[b,SIGMA,RESID]=mvsregress(X,y,nu)

Accelerated Failure Time (AFT) models by Leonidas Bantis

Fits accelerated failure time models in the presence of right and/or left censoring. (accelerated failure t..., aft, survival analysis)

[pars covpars SE CI Zscores pvalues gval exitflag hess fmin...

[pars covpars SE CI Zscores pvalues gval exitflag hess fmin...

[pars covpars SE CI Zscores pvalues gval exitflag hess fmin...

NIST Statistical Reference Datasets for Nonlinear Regression by Adam Gripton

MAT file of all the benchmark Nonlinear Regression problems from the NIST StRD website (nonlinear, regression, statistics)

Plane Fitting and Normal Calculation by Dan Couture

Given a set of x,y,z coordinates, find the best planar fit. (fit, plane, normal)

fitNormal(data, show_graph)

t_fitNormal()

American Monte Carlo by Kienitz Wetterau FinModelling

Algorithms for pricing American Style derivatives with Monte Carlo Simulation (american monte carlo, longstaffscwartz, policy iteration)

...

...

BinTree_A(S0, K, r, T, sigma, n, type)

pregress.m by Elizabeth

A Matlab function pregress.m to carry out linear regression for an arbitrary order n polynomial. (regression, polynomial fit, leastsquares)

pregress( x,y,m );

LOWESS, Locally Weighted Scatterplot Smoothing for linear and non-linear data (enhanced) by Jeff Burkey

LOWESS, a robust regression like LOWESS allows detecton of a trend otherwise with too much variance (weighted regression, robust regression, regression)

lowess(datain,f,wantplot,imagefile,xdata)

New Regression Capabilities in r2012a by Richard Willey

Example code to accompany the "New Regression Capabilities" presentation (2012a regression func..., linear regression, regression)

CurvesSurfaces.m

GLMs.m

Housing.m

Multivariable Polynomial Regression by Ahmet Cecen

Performs polynomial regression on multidimensional data. (polynomial regression, multivariable regress..., statistics)

MultiPolyRegress(Data,R,PW,PV)

polyfitn by John D'Errico

Polynomial modeling in 1 or n dimensions (polyfit, modeling, regression)

polyfitn_demo

polydern(p,diffvar)

polyfitn(indepvar,depvar,modelterms)

Neural Network RBF Regression by Siva Malla

RBF based Neural Network Regression (rbf, neural network, regression)

NeuralNetwork_RBF_Regression.m

Fast & Detailed Multivariate OLS Regression by Léon

Performs a fast multivariate OLS regression and gives detailed information at your fingertips (statistics, finance, mathematics)

aic.m

ci1.m

ci2.m

Theil–Sen estimator by Arnout Tilgenkamp

Robust regression for slope estimation between 1dimensional X and y (linear regression, robust, estimation)

Theil_Sen_Regress(x,y)

PLS regression or discriminant analysis, with leave-one-out cross-validation and prediction. by Cleiton Nunes

M-files for PLS, PLS-DA, with leave-one-out cross-validation and prediction (classification, chemometrics, partial least squares)

pls(x,y,vl,da)

plscv(x,y,vl,da)

plspred(x,model,y)

Linear Deming Regression by James Hall

deming perfoms a linear Deming regression. Useful when errors are present in both x and y variables. (linear regression, regression, orthogonal regression)

deming(x,y,lambda,alpha)

regstats2 by Oleg Komarov

Regstats enhanced. Robust std.errors; loops on a matrix of responses, 'onlydata' model. (error, newey, regstats)

REGSTATS2: what's new

stats=regstats2(responses,data,model,whichstats)

The polynomial regression method by Martin V.

The implementation of polynomial regression method by means of the least square method. (mathematics, statistics, economics)

regPol(order,x,y)

MyRegressionINV by Giuseppe Cardillo

Resolve a calibration problem that is: to estimate mean value and confidence interval of x since y (statistics, probability, inverse)

x=myregrinv(xc,yc,yo,verbose)

Smoothing 2D Contours Using Local Regression Lines by Tolga Birdal

This submission contains both the implementation and the test function for 2D contour smoothing. (smoothing, contour processing, chain codes)

test_smooth_contours()

Interface with Eureqa featuring symbolic regression by Johannes Jenkner

Matlab mex function to call Eureqa server (http://creativemachines.cornell.edu/eureqa) (statistics, eureqa api, regression)

example.m

quantreg.m - quantile regression by Aslak Grinsted

Quantile regression with bootstrapping confidence intervals (percentile, robust fitting, median)

[p,stats]=quantreg(x,y,tau,order,Nboot);

Dynamic Pooled Forecasting by Semin Ibisevic

Dynamic combined forecasting and dynamic principal component regression frameworks. (dynamic, pooled, forecasting)

combinefc(y, Yiv, type, theta, q0)

indivfc(X, y, m, rol, lag, distr)

pcafc(X, y, m, J, Zbin, rol, lag, distr)

Boosted Generalized Additive Models (bgam) package by Patrick Mineault

Boosting for the Generalized Additive and Linear Models (GAM and GLM). (glm, gam, generalized linear mo...)

fitbgam(y,X,trainer,fitParams)

fitcvbgam(y,X,trainer,fitParams,folds)

bgam.CVFit

Optimization Tips and Tricks by John D'Errico

Tips and tricks for use of the optimization toolbox, linear and nonlinear regression. (confidence intervals, examples, tutorial)

optimtips

[x,fval,exitflag,output]=fminsearchbnd(fun,x0,LB,UB,options...

consolidator(x,y,aggregation_mode,tol)

Electricity Load and Price Forecasting Webinar Case Study by Ameya Deoras

Slides and MATLAB® code for the day-ahead system load and price forecasting case study. (artificial intelligen..., electricity load, electricity)

Electricity Load Forecasting using Neural Networks

Electricity Price Forecasting with Neural Networks

Load Forecasting using Bagged Regression Trees

Local Regression 2D by Arnout Tilgenkamp

Local Regression for 2D Data with plot/figure (finance, regression, local regression)

[y0]=MLR(X,y,span,X0,robuust)

Interactive regression on a plot by Ivar Eskerud Smith

Perform regression on plotted data in a figure by manually choosing the regression area. (interactive, regression, polyfit)

figreg( f, n, varargin )

Online/Batch generalized linear models under square loss by Fedor

Online (competitive)/batch prediction using generalized linear models under square loss (regression, mathematics, online prediction)

Assertion function by Malcolm Wood

A function similar to "assert" in C to assist in bug detection (test, testing, tests)

ASSERT(cond,msg)

Robust interpolation by Don MacLeod

1D linear interpolation despite failures of monotonicity in x or y (interpolation, noise, quantization)

robustinterp(Xdata, Ydata, targetX)

LSE by John D'Errico

A linear least squares solver, subject to linear equality constraints (least squares, regression, linear regression)

lse(A,b,C,d,solverflag,weights)

Regression by Arnout Tilgenkamp

Non parametric regression using kernels to estimate density function of residuals. (regression, parametric, nonparametric)

KLMHR2(X,y)

KMLHR(B,X,y)

Kernel Ridge Regression by Ambarish Jash

This is ridge regression implemented using the Gaussian Kernel. (signal processing, statistics, nonlinear)

KernelRidge(in_data,out_data,test_data,lamda)

Linear Median Squared Error by Will Dwinnell

Linear median squared error function for linear functions (statistics, regression, linear regression)

LinearMedianSquaredError(B,X,Y)

MyRegrComp by Giuseppe Cardillo

A simple routine to compare two LS regression (statistics, probability, regression)

myregrcomp(x)

clickfit_OH for curve fitting by eye/hand by Oscar Hartogensis

click a data-series on top of a (noisy) scatterplot and get a spline or polynomial regression (curve fitting, ginput, regression)

clickfit_OH(varargin)

ginput_OH(arg1,strpointertype,xx,yy)

addFitLine by Rob Campbell

A convenience function to superimpose a polynomial fit to already plotted data (plotting, fit, statistics)

out=addFitLine(poolFits,modelType,lineprops,ax)

Beta regression by Willem-Jan de Goeij

Estimation of a beta regression model (logit link function). The parameters are estimated with ML. (beta, regression, model)

betalik(vP, mX, vy)

betareg(vy, mX);

betasim(n, vBeta, phi)

General Least Squares Regression by Husam Aldahiyat

Multi Dimensional Multivariable Least Squares Regression (least, squares, regression)

[fm,C9]=mreg(x,y,m)

Student's t regression by Willem-Jan de Goeij

Estimates a Student's t regression model (studentt, student, t)

betasim(n, vBeta, sigma, nu)

tlik(vP, mX, vy)

treg.m

Gaussian Mixture Model (GMM) - Gaussian Mixture Regression (GMR) by Sylvain Calinon

Encoding of data in Gaussian Mixture Model and retrieval through Gaussian Mixture Regression (gaussian mixture mode..., expecta, gmm)

bbcorr: Bootstrap statistics for Pearson's correlation coefficient by Thomas Maag

Double block bootstrap percentile confidence interval for Pearson's r and Fisher's z. (econometrics, regression, statistics)

[R,Rpc,Rsd,Rpt,Z,Zpc,Zsd,Zpt]=bbcorr(X,reps1,reps2,p,bL,sil...

bbcorrdiff: Bootstrap statistics for the difference of correlation coefficients by Thomas Maag

Double block bootstrap confidence interval for the difference of two correlation coefficients. (econometrics, regression, statistics)

bbcorrdiff(X,reps1,reps2,p,bL,silent)

ACMUB: Median Unbiased Estimation of the AR(p) Model by Thomas Maag

Approximately median unbiased estimation of the AR(p) model following Andrews and Chen (1994). (econometrics, statistics, time series)

[bw,b0,aw,a0]=acmub(Y,p,reps,tol1,tol2,model,silent)