Svam Software Ltd.-

RESELLERS

SUPPORT

Software Marketing >> Statistical Softwares >>

Statistica Advanced Linear/Non-Linear Models offers a wide array of the most advanced linear and nonlinear modeling tools on the market, supports continuous and categorical predictors, interactions, hierarchical models; automatic model selection facilities; also, variance components, time series, and many other methods; all analyses with extensive, interactive graphical support and built-in complete Visual Basic scripting.

Statistica Advanced Linear/Non-Linear Models is compatible with Windows 95, Windows 98, Windows NT, Windows 2000, Windows XP, Windows Me. It features the following modules

Variance Components and Mixed Model ANOVA/ANCOVA
It is a specialized module for designs with random effects and/or factors with many levels

Survival/Failure Time Analysis
This module features a comprehensive implementation of a variety of techniques for analyzing censored data from social, biological, and medical research, as well as procedures used in engineering and marketing.

General Nonlinear Estimation (and Quick Logit/Probit Regression)
The Nonlinear Estimation module allows the user to fit essentially any type of nonlinear model.

Log-Linear Analysis of Frequency Tables
This module offers a complete implementation of log-linear modeling procedures for multi-way frequency tables.

Time Series Analysis/Forecasting
The Time Series module contains a wide range of descriptive, modeling, decomposition, and forecasting methods for both time and frequency domain models.

Structural Equation Modeling/Path Analysis (SEPATH)
It includes a comprehensive implementation of structural equation modeling techniques with flexible Monte Carlo simulation facilities.

General Linear Models (GLM)
General Linear Models (GLM) analyzes responses on one or more continuous dependent variables as a function of one or more categorical or continuous independent variables.

General Regression Models (GRM)
General Regression Models (GRM) provides the user with a unique, highly flexible implementation of the standard and unique results options in the general linear models.

Generalized Linear Models (GLZ)
It allows the user to search for both linear and nonlinear relationships between a response variable and categorical or continuous predictor variables

General Partial Least Squares Models(PLS)
It includes a comprehensive selection of algorithms for univariate and multivariate partial least squares problems.