ABC_P2_norm function

ABC Extimation of P2 for Normal Distribution

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.

ABC_P2_norm(n, ObsMean, M_Lo, M_Hi, SD_Lo, SD_Hi, delta, iter)

Arguments

• n: number of observations.
• ObsMean: 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.

Returns

• 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)