Search
Code Directory
 ASP
 ASP.NET
 C/C++
 CFML
 CGI/PERL
 Delphi
 Development
 Flash
 HTML
 Java
 JavaScript
 Pascal
 PHP
 Python
 SQL
 Tools
 Visual Basic & VB.NET
 XML
New Code
iScripts DailyDeals 1.0
Silverlight .NET Video Capture SDK 1.7
wolfSSL 3.10.2
GraphicsJS 1.2.0
Feedback Form Script by PHPJabbers 1.0
Metamill 8.0.1820
C# Web Scraping Library 4.0.4.2
Appointment Scheduling Software 2.0
AnyStock Stock and Financial JS Charts 7.13.0
VISCOM 3D Carousel SDK ActiveX 2.45
Excel Add-in for FreshBooks 1.6
Excel Add-in for Dynamics CRM 1.6
TeeGrid 1.0
iScripts CyberMatch 1.3
iScripts UberforX 2.0
Top Code
Magento Product Designer 1.0
Restaurant Ordering Software 1.5
OFOS - Just Eat Clone Script 1.0
PrestaShop Upload Images Module 1.2.1
Trading Software 1.2.4
Solid File System OS edition 5.1
Classified Ad Lister 1.0
Aglowsoft SQL Query Tools 8.2
dbForge Studio for SQL Server Express 5.0
Image Editor Using JavaFX 1.0
Sine Wave Using JavaFX 1.0
ICPennyBid Penny Auction Script 4.0
PHP Review Script 1.0
ATN Resume Finder 2.0
ATN Site Builder 3.0
Top Search
Code To Add Url
Photo Add Comment Php
Contoh Program Registrasi Dalam Java
Dirty Word
Twitter Update Script Php
Photo Gallery Comment Php
Free Tutorials Php Mysql Appointment Calendars Sms
Sample Emcee Script For Coronation Rites
Free Html Projects
Html Projects For Students Free Download
Advance Java Mini Projects
Free Prepaid Electricity Meter Generator Download
Sample Script Of Recognition Day Public School
Code Guestbook
Energy Billing System Code In Java
Related Search
Stata Regress
Straight Line Regress
 Regress 

Code 1-10 of 10   






Helps choose a Box-Cox power transformation for a multivariate linear regression.

Assume you are looking at the residuals of [b,bint,r] = regress(y,X) and it seems a transformation is in place. Use:
boxcoxlm(y,X) to find the best lambda for a Box-Cox power transformation (y^lambda, or log(y) for lambda=0)

The function will also plot the Maximum Log-Likelihood as a function of lambda, and a 95% confidence region for...



% Original model: y = X*beta + u
% We are concerned that a regressor in X
% could be endogenous.
% W contains the instruments and all regressors in X
% except the suspected one.

% An example:
% m_t = b1 + b2*r_t...



2.5 brought many great UI changes, but a few seem unfounded and, in my opinion, were steps backward. I've never been a fan of left-aligned interfaces. This plugin resets the interface to the center of the window. All proper credit to "Remove...



Object Oriented Report Writer.

The AIM ReportFactory enables you to integrate a completely object-oriented reporting interface, featuring Drag&Drop, into your own products. Thereby the programmer can alleviate the users from using...



The units MATH1, MATH2, MATRIX, and STATIS, which are part of the SDL Component Suite, offer some of the most fundamental procedures of mathematical statistics. These units offer a large number of classes and routines from basic statistics to...



This component enables you to integrate an object-oriented reporting interface into your own software.By using it the separation between a report designer, a report viewer and a print preview becomes dispensable. The WYSIWYG interface displays...



The basic iterator for a list is a very "fast-but-dumb" design. It doesn't allow one to skip forward (except with "continue"), or backward (at all), nor does it behave well if the list is modified while it is being traversed....



The stats toolbox is required for the 'linear' and 'quadratic' options only.

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

Purpose
Add one or more fit lines to some or all data in axes "ax" or,



ORTHLLS2D returns the Orthogonal Linear Least Squares estimate for parameters of line a x + b y + c = 0

function f = OrthLLS2D(x, y)

Inputs x and y must be real vectors of equal size.
Output f is the real vector [a b c]...



TESTHET Tests wether heteroskedasticity affects data. Need 'regstats' and 'chi2cdf' (Stat TB).

PVAL = TESTHET(RES, X, WHICHTEST, YHAT)
INPUTS:
- Res: residuals obtained by regressing Y on x1, x2 etc...(1) It can be a numeric...