Transcription of Fitting distributions with R
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Fitting distributions with R
Fitting distributions with R 1 Fitting distributions WITH R Release February 2005 Vito Ricci Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version or any later version published by the Free Software Foundation: #FDL Copyright 2005 Vito Ricci Fitting distributions with R 2 TABLE OF CONTENTS Introduction Graphics Model choice Parameters estimate Measures of goodness of fit Goodness of fit tests Normality tests Appendix: List of R statements useful for distributions Fitting References Fitting distributions with R 3 Introduction Fitting distributions consists in finding a mathematical function which represents in a good way a statistical variable. A statistician often is facing with this problem: he has some observations of a quantitative character x1, x2.
For each distribution there is the graphic shape and R statements to get graphics. Dealing with discrete data we can refer to Poisson’s distribution7 (Fig. 6) with probability mass function: ! ( , ) x f x e lx l =-l where x=0,1,2,… x.poi<-rpois(n=200,lambda=2.5) hist(x.poi,main="Poisson distribution") As concern continuous data we have:
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