# strata.distr: Stratification of Univariate Survey Population Using the... In stratifyR: Optimal Stratification of Univariate Populations

## Description

This function takes in the underlying hypothetical distribution and its parameter(s) of the survey variable, the initial value and the range of the population, the fixed sample size (n) and the fixed population size (N) to compute the optimum stratum boundaries (OSB) for a given number of strata (L), optimum sample sizes (nh), etc. The main idea used is from Khan et al. (2008) whereby the problem of stratification is fromulated into a Mathematical Programming Problem (MPP) using the best-fit frequency distribution and its parameter estimates of the data. This MPP is then solved for the optimal solutions using the Dynamic Programming (DP) solution procedure.

## Usage

 1 2 3 4 5 6 7 8 9 10 11 12 13 strata.distr( h, initval, dist, distr = c("pareto", "triangle", "rtriangle", "weibull", "gamma", "exp", "unif", "norm", "lnorm", "cauchy"), params = c(shape = 0, scale = 0, rate = 0, gamma = 0, location = 0, mean = 0, sd = 0, meanlog = 0, sdlog = 0, min = 0, max = 0, mode = 0), n, N, cost = FALSE, ch = NULL )

## Arguments

 h A numeric: denotes the number of strata to be created. initval A numeric: denotes the initial value of the population dist A numeric: denotes distance (or range) of the population distr A character: denotes the name of the distribution that characterizes the population params A list: contains the values of all parameters of the distribution n A numeric: denotes the fixed total sample size. N A numeric: denotes the fixed total population size. cost A logical: has default cost=FALSE. If it is a stratum-cost problem, cost=TRUE, with which one must provide the Ch parameter. ch A numeric: denotes a vector of stratum costs.

## Value

strata.distr returns Optimum Strata Boundaries (OSB), stratum weights (Wh), stratum costs (Ch), stratum variances (Vh), Optimum Sample Sizes (nh), stratum population sizes (Nh).

## Author(s)

Karuna Reddy <karuna.reddy@usp.ac.fj>
MGM Khan <khan_mg@usp.ac.fj>