Description Usage Arguments Value Examples
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)
1 2 3 | population_sampling(maxent_predict_raw, maxent_predict_logis,
region = c("ITA"), species, N, month_logis_base, month, graph_logis = F,
graph_raw = F)
|
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 |
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
1 2 3 4 5 6 7 8 9 10 11 | # 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")
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