simPopInternal  R Documentation 
Functions for calculating valuable quantities and for drawing from important distributions for population simulation.
getExpectedNperEA(easpa, popMat, level = c("grid", "EA"), pixelIndexMat = NULL)
getSortIndices(
i,
urban = TRUE,
popMat,
stratifyByUrban = TRUE,
validationPixelI = NULL
)
rStratifiedMultnomial(n, popMat, easpa, stratifyByUrban = TRUE)
rStratifiedMultnomialBySubarea(
n,
popMat,
easpa,
stratifyByUrban = TRUE,
poppsub = NULL,
min1PerSubarea = TRUE,
minSample = 1
)
rMyMultinomial(
n,
i,
stratifyByUrban = TRUE,
urban = TRUE,
popMat = NULL,
easpa = NULL,
min1PerSubarea = FALSE,
method = c("mult1", "mult", "indepMH"),
minSample = 1
)
rMyMultinomialSubarea(
n,
i,
easpsub,
stratifyByUrban = TRUE,
urban = TRUE,
popMat = NULL
)
rmultinom1(
n = 1,
size,
prob,
maxSize = 8000 * 8000,
method = c("mult1", "mult", "indepMH"),
verbose = FALSE,
minSample = 100,
maxExpectedSizeBeforeSwitch = 1000 * 1e+07,
init = NULL,
burnIn = floor(n/4),
filterEvery = 10,
zeroProbZeroSamples = TRUE,
allowSizeLessThanK = FALSE
)
sampleNMultilevelMultinomial(
nDraws = ncol(pixelIndexMat),
pixelIndexMat = NULL,
urbanMat = NULL,
areaMat = NULL,
easpaList,
popMat,
stratifyByUrban = TRUE,
verbose = TRUE,
returnEAinfo = FALSE,
minHHPerEA = 25,
fixHHPerEA = NULL,
fixPopPerHH = NULL
)
sampleNMultilevelMultinomialFixed(
clustersPerPixel,
nDraws = ncol(pixelIndices),
pixelIndices = NULL,
urbanVals = NULL,
areaVals = NULL,
easpa,
popMat,
stratifyByUrban = TRUE,
verbose = TRUE
)
easpa 
Census frame. See 
popMat 
data.frame of pixellated grid of population densities. See 
level 
Whether to calculate results at the integration grid or EA level 
pixelIndexMat 
Matrix of pixel indices associated with each EA and draw. Not required by getExpectedNperEA unless level == "EA" 
i 
Index 
urban 
If TRUE, calculate only for urban part of the area. If FALSE, for only rural part 
stratifyByUrban 
whether or not to stratify calculations by urban/rural classification 
validationPixelI 
CURRENTLY FOR TESTING PURPOSES ONLY a set of indices of pixels for which we want to simulate populations (used for pixel level validation) 
n 
Number of samples 
poppsub 
Population per subarea. See 
min1PerSubarea 
Whether or not to ensure there is at least 1 EA per subarea. See 
minSample 
The minimum number of samples per 'chunk' of samples for truncated multinomial sampling. Defaults to 1 
method 
If min1PerSubarea is TRUE, the sampling method for the truncated multinomial to use with rmulitnom1. rmultinom1 automatically switches between them depending on the number of expected samples. The methods are:

easpsub 
This could either be total EAs per subarea, or subarea crossed with urban or rural if stratifyByUrban is TRUE 
size 
Multinomial size parameter. See 
prob 
Multinomial probability vector parameter. See 
maxSize 
The maximum number of elements in a matrix drawn from the proposal distribution per sample chunk. 
verbose 
Whether to print progress as the function proceeds 
maxExpectedSizeBeforeSwitch 
Max expected number of samples / k, the number of categories, before switching method 
init 
Initial sample if method is 'indepMH' 
burnIn 
Number of initial samples before samples are collected if method is 'indepMH' 
filterEvery 
Store only every filterEvery samples if method is i'indepMH' 
zeroProbZeroSamples 
If TRUE, set samples for parts of prob vector that are zero to zero. Otherwise they are set to one. 
allowSizeLessThanK 
If TRUE, then if size < the number of categories (k), returns matrix where each column is vector of size ones and k  size zeros. If FALSE, throws an error if size < k 
nDraws 
Number of draws 
urbanMat 
Matrix of urbanicities associated with each EA and draw 
areaMat 
Matrix of areas associated with each EA and draw 
easpaList 
A list of length n with each element being of the format of easpa giving the number of households and EAs per stratum. It is assumed that the number of EAs per stratum is the same in each list element. If easpaList is a data frame, number of households per stratum is assumed constant 
returnEAinfo 
Whether a data frame at the EA level is desired 
minHHPerEA 
The minimum number of households per EA (defaults to 25, since that is the number of households sampled per DHS cluster) 
fixHHPerEA 
If not NULL, the fixed number of households per EA 
fixPopPerHH 
If not NULL, the fixed target population per household 
clustersPerPixel 
CURRENTLY FOR TESTING PURPOSES ONLY a vector of length nIntegrationPoints specifying the number of clusters per pixel if they are fixed 
pixelIndices 
A nEA x n matrix of pixel indices associated with each EA per simulation/draw 
urbanVals 
A nEA x n matrix of urbanicities associated with each EA per simulation/draw 
areaVals 
A nEA x n matrix of area names associated with each EA per simulation/draw 
getExpectedNperEA()
: Calculates expected denominator per enumeration area.
getSortIndices()
: For recombining separate multinomials into the draws over all grid points
rStratifiedMultnomial()
: Gives nIntegrationPoints x n matrix of draws from the stratified multinomial with values
corresponding to the value of C^g for each pixel, g (the number of EAs/pixel)
rStratifiedMultnomialBySubarea()
: Gives nIntegrationPoints x n matrix of draws from the stratified multinomial with values
rMyMultinomial()
:
rMyMultinomialSubarea()
:
rmultinom1()
: Random (truncated) multinomial draws conditional on the number of each type being at least one
sampleNMultilevelMultinomial()
: Take multilevel multinomial draws first from joint distribution of
number of households per EA given the total per stratum, and then from the joint
distribution of the total target population per household given
the total per stratum
sampleNMultilevelMultinomialFixed()
: Same as sampleNMultilevelMultinomial, except the number of EAs per pixel is fixed
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