get_optim: Find PDF optim(a)um

In rsh249/CRACLE: Climate Reconstruction Analysis using Coexistence Likelihood Estimation

Description

Using an object from the cRacle::dens_obj() function. Create a single density object (i.e., like that produced by cRacle::densform()) where the probability curves correspond to the probability density function of ALL taxa/species from the original set occurring.

Usage

get_optim(dens.ob)

Arguments

dens.ob

An object derived from the cRacle::dens_ob() function.

Value

A list with letters and numbers.

• conintkde - 95

• conintgauss- 95

• origk - Kernel density optimal interval as in Harbert & Nixon, 2015. Within 1 percent of the maximal likelihood.

• origg - Gaussiandensity optimal interval as in Harbert & Nixon, 2015. Within 1 percent of the maximal likelihood.

• dirconint - Direct calculation of the gaussian based confidence interval using weighted means. Should be identical to conintgauss.

• means - Weighted means, Should be the same as the maximally likely value of the gaussian density curve.

• sds - Weighted standard deviation.

Examples

## Not run: 
#distr <- read.table('test_mat.txt', head=T, sep ="\t");
#OR:
data(distr);
data(climondbioclim);
extr.raw = extraction(data=distr, clim= climondbioclim, schema='raw');
dens.list.raw <- dens_obj(extr.raw, clim = climondbioclim, bw = 'nrd0', n = 1024);
multiplot(dens.list.raw, names(climondbioclim[[1]]));
and <- and_fun(dens.list.raw);
addplot(and, names(climondbioclim[[1]]), col ='black');
optim.and <- get_optim(and);
abline(v=optim.and$means[paste(names(climondbioclim[[1]]), 'mean', sep = ".") ])

## End(Not run)

rsh249/CRACLE documentation built on Feb. 2, 2022, 11:31 p.m.