This function fits offspring data to a special case of the normal distribution, in which zero and negative values of offspring are excluded, and estimates P2 based on that distribution and the specificed priors.
the observed mean number of offspring sired by the second male.
M_Lo
minimum mean value for the distribution.
M_Hi
maximum mean value for the distribution.
SD_Lo
minimum standard deviation value for the distribution.
SD_Hi
maximum standard deviation value for the distribution.
delta
maximum allowed difference between the estimated mean and observed mean number of offspring produced by the second male.
iter
number of iterations used to build the posterior.
Value
posterior
Posterior distribution of P2 values.
Avg
Vector of values for the mean parameter.
Std
Vector of values for the standard deviation parameter.
Author(s)
M. Catherine Duryea, Andrew D. Kern, Robert M. Cox, and Ryan Calsbeek
Examples
#Fit the Mean and Standard Deviation hyperpriors to a distribution of offspring.
data(fungus)
fit_dist_norm(fungus$Total_Offspring)
#Use hyperiors and priors calculated from the data to estimate P2.
#Plot the saved distributions for the Mean and Standard Deviation parameters.
#Adjust, if necessary.
fungus_P2<-ABC_P2_norm(12, 9.9, 11.35, 17.31, 8.22, 12.44, 0.1, 100)
hist(fungus_P2$posterior)
hist(fungus_P2$Avg)
hist(fungus_P2$Std)
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(ABCp2)
Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ABCp2/ABC_P2_norm.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ABC_P2_norm
> ### Title: ABC Extimation of P2 for Normal Distribution
> ### Aliases: ABC_P2_norm
> ### Keywords: ~kwd1 ~kwd2
>
> ### ** Examples
>
> #Fit the Mean and Standard Deviation hyperpriors to a distribution of offspring.
>
> data(fungus)
> fit_dist_norm(fungus$Total_Offspring)
$data_norm
[1] 11 10 9 13 4 38 22 10 19 36 8 20
$fit_norm
mean sd
14.333333 10.330645
( 2.982200) ( 2.108734)
$chi_norm
Pearson's Chi-squared test
data: dist and data_norm
X-squared = 63, df = 60, p-value = 0.3707
Warning message:
In chisq.test(dist, data_norm) : Chi-squared approximation may be incorrect
>
> #Use hyperiors and priors calculated from the data to estimate P2.
> #Plot the saved distributions for the Mean and Standard Deviation parameters.
> #Adjust, if necessary.
>
> fungus_P2<-ABC_P2_norm(12, 9.9, 11.35, 17.31, 8.22, 12.44, 0.1, 100)
> hist(fungus_P2$posterior)
> hist(fungus_P2$Avg)
> hist(fungus_P2$Std)
>
>
>
>
>
>
> dev.off()
null device
1
>
providing 
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