population_sampling: population_sampling

Description Usage Arguments Value Examples

Description

Given a specific region and month, population_sampling function zooms in on the probability distributions in the region, calculates its average logistic probabilities and calculate the corresponding sample size for the given month (based on the ratio of mean logistic probabilities in the given month and the reference month)

Usage

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population_sampling(maxent_predict_raw, maxent_predict_logis,
  region = c("ITA"), species, N, month_logis_base, month, graph_logis = F,
  graph_raw = F)

Arguments

maxent_predict_raw

global raw probabilities raster for the given month

maxent_predict_logis

global logistic probabilities raster for the given month

region

a vector of region names specifying a region of interest from national levels down to county levels

species

a vector containing genus and species name

N

number of species samples to draw in the reference month

month_logis_base

global logistic probabilities raster for the reference month

month

an interger (1-12) indicating the month of interest

Value

month_samples: sample points (spatial points) drawn from the given month

month_region_log: logistic probability raster of the given region in given month

month_N: the number of samples (integer) drawn from the given month proportional to the sample size from the reference month

Examples

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# Example: draw a sample of 2000 mosquitos from Pennsylvania
sampling_results <- population_sampling(mosquito_predictions_6$raw,
mosquito_predictions_6$logis,
region=c("USA", "Pennsylvania"),
species=c("aedes", "aegypti"), 
N=2000,
month_logis_base=mosquito_predictions_6$logis, 
month=6, graph_logis=T, graph_raw=T) 
plot(sampling_results$month_region_log)
points(sampling_results$month_samples, cex=0.5, pch=16, col="blue")
title("Logistic Probabilities and Aedes Aegypti Population Sampling for PA")

elaineliu5/DVM documentation built on May 16, 2019, 2:57 a.m.