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Redundancy analysis (RDA)

What is Redundancy Analysis Redundancy Analysis (RDA) was developed by Van den Wollenberg (1977) as an alternative to Canonical Correlation Analysis (CCorA). Redundancy Analysis allows studying the relationship between two tables of variables Y and X. While the Canonical Correlation Analysis is a symmetric method, Redundancy Analysis is non-symmetric. In Canonical Correlation Analysis, the components...

Classification and regression random forests

What is a Random Forest Random forests provide predictive models for classification and regression. The method implements binary decision trees, in particular, CART trees proposed by Breiman et al. (1984). In classification (qualitative response variable): The model allows predicting the belonging of observations to a class, on the basis of explanatory quantitative and/or qualitative variables. In...

Tests on contingency tables

What are tests on contingency tables? Tests on contingency tables are used to evaluate the association and the independence between the rows and the columns of a contingency table as well as to calculate various association measures. Tests of independence between the rows and the columns of a contingency table in XLSTAT The Pearson chi-square statistic allows to test the independence between the rows...

Gaussian mixture models

What are the Gaussian mixture models? Mixture modeling were first mentioned by Pearson in 1894 but their development is mainly due to the EM algorithm (Expectation Maximization) of Dempster et al. in 1978. These models are commonly used for a clustering purpose. They can provide a framework for assessing the partitions of the data by considering that each component represents a cluster. These models...

Cochran's Q test in Excel tutorial

Homogeneity tests for time series

What are homogeneity tests for time series Homogeneity tests enables you to determine if a series may be considered as homogeneous over time, or if there is a time at which a change occurs. Homogeneity tests involve a large number of tests, XLSTAT offer four tests (Pettitt, Buishand, SNHT, or von Neumann), for which the null hypothesis is that a time series is homogenous between two given times. The...

Logistic regression (Binary, Ordinal, Multinomial, …)

Definition of the logistic regression in XLSTAT Principle of the logistic regression Logistic regression is a frequently used method because it allows to model binomial (typically binary) variables, multinomial variables (qualitative variables with more than two categories) or ordinal (qualitative variables whose categories can be ordered). It is widely used in the medical field, in sociology, in...

CATA data analysis

What is CATA (check-all-that-apply) analysis? CATA (check-all-that-apply) surveys have become more and more popular for sensory product characterization since 2007, when it was presented by Adams et al. CATA surveys allow to focus on consumers, more representative of the market, instead of trained assessors. They are easy to set up and easy for participants to answer. The principle is that each assessor...

Monte Carlo simulations

What is a Monte Carlo Simulation in XLSTAT? Monte Carlo Simulation is a module that allows building and computing simulation models, an innovative method for estimating variables, whose exact value is not known, but that can be estimated by means of repeated simulation of random variables that follow certain theoretical laws. Before running the model, you need to create the model, defining a series...

Subgroup charts

What is a subgroup control chart A subgroup chart is a type of control chart that focus on the quality characteristic measurement within one subgroup. It is used to supervise production quality, in the case where you have a group of measurements for each point in time. The measurements need to be quantitative data. This tool is useful to recap the mean and the variability of the measured production...