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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...

Principal component analysis (PCA) in Excel

Generalized Procrustes Analysis (GPA)

When to use Generalized Procrustes Analysis Generalized Procrustean Analysis (GPA) is used in sensory data analysis prior to a Preference Mapping to reduce the scale effects and to obtain a consensual configuration. It also allows comparing the proximity between the terms that are used by different experts to describe products. Principle of Generalized Procrustes Analysis We define by configuration...

Save and reuse settings of an analysis, example of Principal Component Analysis

Automate a routine analysis, example of Principal Component Analysis, in XLSTAT

Time series transformation

XLSTAT offers four different possibilities for transforming a time series Xt into Yt, (t=1,…,n): Box-Cox transform (fixed or optimised) Box-Cox transformation is used to improve the normality of the time series; the Box-Cox transformation is defined by the following equation: Yt = [ ( X2t - 1 ) / λ , (Xt > 0, λ ≠ 0 ) or (Xt ≥ 0, λ > 0 ) ; ln( Xt ), (Xt > 0, λ = 0) ] XLSTAT accepts a fixed value of...

XLSTAT Essentials

Build a strong statistical foundation with XLSTAT Essentials XLSTAT Essentials is the ideal starting point for business analysts, data analysts, and quality control professionals seeking a powerful, yet affordable statistical solution. With 100+ core statistical tools, it enables data preparation, visualization, hypothesis testing, and modeling—all within the familiar Microsoft Excel environment....

Smoothing of time series

Several smoothing methods are available in the XLSTAT-Forecast solution. They are described below. Simple exponential smoothing This model is sometimes referred to as Brown's Simple Exponential Smoothing, or the exponentially weighted moving average model. Exponential smoothing is useful when one needs to model a value by simply taking into account past observations. It is called "exponential" because...

Welch and Brown-Forsythe one-way ANOVA

The analysis of variance (ANOVA) allows to determine whether a factor, also called explanatory variable, has a significant effect on a dependent variable. For example, we may test the effects of a factor involving 4 medical treatments on blood pressure. Running a one-way ANOVA on the data would answer the question: “is there at least one treatment which significantly differs from the others? Principles...

Dose effect analysis

What is dose effect analysis Dose effect analysis is simply a Logistic regression (Logit, Probit, complementary Log-log, Gompertz models) used to model the impact of doses of chemical components (for example a medicine or phytosanitary product) on a binary phenomenon (healing, death). Natural mortality in dose effect analysis Natural mortality should be taken into account in order to model the phenomenon...