fit_dist_norm: Fit Offspring Distribution to the Normal Distribution

In ABCp2: Approximate Bayesian Computational Model for Estimating P2

Description

This function fits offspring data to a special case of the normal distribution, in which zero and negative values of offspring are excluded, and tests the goodness of fit using the chi-squared test.

Usage

fit_dist_norm(dist)

Arguments

dist	a numeric vector of data values for number of offspring per dam.

Value

estimate	Mean and standard deviation parameters estimated from the supplied distribution.
sd	Standard deviation of the mean and standard deviation estimates.
vcov	Variance/covariance matrix of the mean and standard deviation estimates.
loglik	the log-likelihood of the mean and standard deviation estimates.
n	The number of observations.
statistic	The chi-squared test statistic.
parameter	Degrees of freedom for the chi-squared test.
p.value	P-value for the chi-squared test.
data_norm	Vector of values generated from a special case of the normal distribution.

Author(s)

M. Catherine Duryea, Andrew D. Kern, Robert M. Cox, and Ryan Calsbeek

Examples

#Fit the Mean and Standard Deviation parameters to a distribution of offspring.
#Test the goodness of fit.

data(fungus)
fungus_fit<-fit_dist_norm(fungus$Total_Offspring)
fungus_fit$fit_norm
fungus_fit$chi_norm
fungus_fit$data_norm

Example output

Loading required package: MASS
Warning message:
In chisq.test(dist, data_norm) : Chi-squared approximation may be incorrect
     mean         sd    
  14.333333   10.330645 
 ( 2.982200) ( 2.108734)

	Pearson's Chi-squared test

data:  dist and data_norm
X-squared = 54, df = 48, p-value = 0.2559

 [1]  6 31 21 15 11  7 27 15  7  8 21 13

ABCp2 documentation built on May 1, 2019, 6:31 p.m.