Last data update: 2014.03.03

 R: Summarizing Gamma Shape Mixtures
summary-methodsR Documentation

Summarizing Gamma Shape Mixtures

Description

summary method for class "gsm". This function allows to summarize the output of a Gamma Shape Mixture estimate procedure like estim.gsm or estim.gsm_theta.

Usage

## S4 method for signature 'gsm'
summary(object, plot = FALSE, start = 1, ...)

Arguments

object

object of class "gsm"; a list returned by the estim.gsm or estim.gsm_theta functions.

plot

logical; if TRUE produces a bar plot of the mixture weights posterior means.

start

MCMC run to start from.

...

further arguments passed to or from other methods.

Value

The function summary computes and returns a list of summary statistics of the fitted gamma shape mixture given in object, in particular

theta

summary index of the theta parameter posterior draws.

weight posterior means

vector of the mixture weights posterior means.

Author(s)

Sergio Venturini sergio.venturini@unibocconi.it

References

Venturini, S., Dominici, F. and Parmigiani, G. (2008), "Gamma shape mixtures for heavy-tailed distributions". Annals of Applied Statistics, Volume 2, Number 2, 756–776. http://projecteuclid.org/euclid.aoas/1215118537

See Also

estim.gsm, estim.gsm_theta, plot-methods, predict-methods.

Examples

set.seed(2040)
y <- rgsm(500, c(.1, .3, .4, .2), 1)
burnin <- 5
mcmcsim <- 10
J <- 250
gsm.out <- estim.gsm(y, J, 300, burnin + mcmcsim, 6500, 340, 1/J)
summary(gsm.out, TRUE, start = (burnin + 1))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(GSM)
Loading required package: gtools
Package GSM (1.3.2) loaded.
To cite, see citation("GSM")

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/GSM/summary-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: summary-methods
> ### Title: Summarizing Gamma Shape Mixtures
> ### Aliases: summary-methods summary,ANY-method summary,gsm-method
> ### Keywords: methods
> 
> ### ** Examples
> 
> set.seed(2040)
> y <- rgsm(500, c(.1, .3, .4, .2), 1)
> burnin <- 5
> mcmcsim <- 10
> J <- 250
> gsm.out <- estim.gsm(y, J, 300, burnin + mcmcsim, 6500, 340, 1/J)
> summary(gsm.out, TRUE, start = (burnin + 1))
$theta
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  17.79   18.31   18.43   18.41   18.62   18.82 

$`weights posterior means`
  [1]  5.640294e-03  1.035467e-07  9.331575e-03  2.107689e-02  1.278341e-17
  [6]  1.723509e-04  1.187973e-03  1.668403e-03  6.974614e-13  1.181297e-02
 [11]  1.554602e-02  1.926430e-02  1.072475e-02  4.556410e-06  3.269905e-02
 [16]  1.512589e-02  6.782652e-02  4.097396e-04  1.871555e-28  2.372725e-31
 [21]  2.010538e-02  4.013180e-14  9.998780e-03  1.779756e-02  9.609256e-04
 [26]  1.150933e-02  1.531516e-02  1.656345e-02  4.650400e-02  1.648407e-02
 [31]  1.611121e-02  1.148362e-15  1.919959e-02  3.805913e-05  2.860609e-02
 [36]  9.261294e-23  1.082085e-03  1.994877e-15  9.492225e-05  2.931719e-12
 [41]  1.645737e-02  2.519270e-02  2.521191e-02  2.198388e-03  1.109902e-03
 [46]  4.735439e-02  7.987928e-04  2.851525e-03  5.424614e-06  6.174439e-02
 [51]  1.006378e-08  9.909390e-05  7.071610e-23  1.395890e-32  3.061429e-07
 [56]  7.375437e-08  3.457307e-02  2.047107e-02  3.583573e-02  1.151859e-08
 [61]  9.796217e-50  8.592421e-24  1.035068e-02  7.819128e-06  1.225139e-02
 [66]  3.481828e-28  3.073019e-04  3.181812e-06  9.100665e-16  1.149941e-06
 [71]  1.216603e-07  3.489321e-10  1.343994e-11  5.445605e-12  8.392418e-12
 [76]  4.312031e-15  3.705499e-22  4.268674e-02  1.350991e-01  7.147971e-15
 [81]  1.333574e-19  8.933987e-08  4.097953e-12  2.291558e-34  1.011522e-15
 [86]  7.748782e-31  3.470287e-05  4.390490e-43  5.908965e-33  7.478927e-13
 [91]  1.050794e-07  6.241327e-08  9.195569e-12  2.614734e-51  2.310143e-27
 [96]  5.668295e-17  1.029785e-42  4.657320e-12  8.280673e-10  1.022066e-20
[101]  1.991292e-14  3.225170e-10  2.754497e-14  3.465117e-21  2.614593e-19
[106]  1.716831e-15  1.985842e-15  4.572791e-26  3.602109e-19  2.736702e-28
[111]  4.375620e-06  4.622587e-16  2.886720e-19  7.983634e-02  8.637559e-05
[116]  1.967546e-31  2.449504e-72  1.157779e-06  6.290667e-06  7.046564e-35
[121]  8.153096e-07  1.608795e-10  1.531765e-31  1.275092e-46  5.467911e-06
[126]  4.007545e-17  3.340262e-04  7.612699e-07  1.375524e-07  1.662906e-14
[131]  9.788497e-07  3.567672e-13  8.057097e-09  2.231069e-18  4.274106e-09
[136]  2.759670e-22  1.056429e-21  1.141439e-37  1.336761e-15  4.844432e-08
[141]  2.559535e-07  7.872523e-21  1.892542e-16  1.312676e-05  4.444049e-05
[146]  4.888660e-20  2.315894e-05  4.648334e-05  7.275623e-06  6.462810e-35
[151]  6.236775e-13  2.022994e-10  1.236983e-46  4.487614e-05  2.316333e-30
[156]  6.507342e-03  1.251441e-09  9.012862e-18  9.222381e-29  1.430860e-16
[161]  3.658650e-07  2.846020e-10  2.685909e-10  1.055975e-14  9.081172e-24
[166]  3.602976e-05  4.451507e-17  2.088070e-18  7.932004e-23  4.006776e-28
[171]  3.508968e-13  6.696234e-09  8.487769e-07  7.459509e-12  2.540722e-06
[176]  3.588153e-09  6.537331e-26  1.066944e-06  2.581627e-06  1.661691e-06
[181]  9.027826e-26  5.594969e-20  1.826051e-46  5.027805e-03  7.370701e-11
[186]  9.070957e-11  9.195099e-06  1.677399e-08  9.989574e-29  1.515357e-07
[191]  5.962000e-10  2.063747e-10  3.328388e-14  8.956063e-07  1.667170e-25
[196]  8.029841e-08  3.530553e-11  6.450396e-19  8.522499e-17  2.088905e-17
[201]  3.194125e-24  3.577845e-21  2.922142e-08  6.852090e-10  2.437974e-08
[206]  1.855225e-40  1.907052e-32  6.295361e-10  9.191927e-06  3.364855e-08
[211]  1.016846e-04  4.796383e-24  7.089511e-26  5.046428e-15  1.803170e-19
[216]  7.661832e-24  1.988108e-25  8.881100e-36  1.523250e-21  3.575806e-20
[221]  1.217115e-16  1.588962e-05  8.624718e-05  2.117330e-21  1.586584e-12
[226]  1.188838e-16  3.317507e-10  3.090680e-24 8.840291e-102  2.939901e-08
[231]  3.741823e-11  5.753588e-05  7.792128e-78  1.302709e-07  1.304924e-20
[236]  7.557551e-05  6.086630e-05  4.141813e-09  1.200798e-21  1.576577e-18
[241]  3.135659e-38  1.526303e-14  1.357293e-12  3.711840e-05  8.516211e-18
[246]  7.637924e-19  1.176402e-17  5.260328e-13  1.874541e-10  1.625057e-13

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


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