simul_IC_exp: Calculates exposure indices and simulates confidence...

In Nmoiroux/biteExp:

Description

Calculates exposure indices and simulates confidence intervals based on bootstraping methods

Usage

simul_IC_exp(DataExp, p = 0.92, ndays = 1, nsim = 5000, tE = 10,
  tM = 18)

Arguments

DataExp	a dataframe obtained by the use of function 'exposure_dat'
p	the personal protection provided by an LLIN (default = 0.92 for Permanet 2 according to Corbel et al. 2010)
ndays	duration (in days) of collection during each survey in each collection point (default = 1)
nsim	number of simulations (default = 5000)
tE	upper limit hour for evening exposure calculation, in a referential with 12h as origin (i.e 10 corresponds to 22h)
tM	lower limit hour for morning exposure calculation, in a referential with 12h as origin (i.e 18 corresponds to 6h)

Value

a dataframe with 7 columns : "Vil" village code (factor) "Enq" survey number (integer) "Age" age classes (factor) "var_exp" name of the calculated exposure variable (Eff, Peui, Peuni, PeuE, PeneE, PeuM, PenuM) (factor) "mean" mean value (real) "lo95" lower bound of 95 "hi95" higer bound of 95

Examples

Count_HB <- HB_to_counts(ODK_HB_R)
Count_HB$Enq <- 1
Data_Entomo <- Entomo_PHP_to_counts(Entomo_PHP)
Exposure <- exposure_dat(Count_HB, Data_Entomo, p = 0.92)
exp_CI <- simul_IC_exp(Exposure, p = 0.92, ndays = 1, nsim = 5000, tE = 10, tM = 18)

Nmoiroux/biteExp documentation built on March 13, 2020, 10:39 p.m.