1d:T6bf,# Plot of the sensitivity analysis for some parameters by means of grid search This function allows to plot the results of the simulation carried out by using the function 'sensitivity'. ```r plot_sens ( x, min, max) ``` ## Arguments - `x`: The result of the 'sensitivity' function. - `min`: minimum value of the parameter. - `max`: maximum value of the parameter. ## Returns A list containing the (i) vector of allocated PSUs in the iterations and (ii) the vector of allocated SSUs in the iterations ## Examples ```r ## Not run: library(readr) pop <- read_rds("https://github.com/barcaroli/R2BEAT_workflows/blob/master/pop.RDS?raw=true") library(R2BEAT) cv <- as.data.frame(list(DOM=c("DOM1","DOM2"), CV1=c(0.02,0.03), CV2=c(0.03,0.05), CV3=c(0.03,0.05), CV4=c(0.04,0.08))) cv # parameters samp_frame <- pop errors <- cv id_PSU <- "municipality" id_SSU <- "id_ind" strata_var <- "stratum" target_vars <- c("income_hh","active","inactive","unemployed") # more than one deff_var <- "stratum" domain_var <- "region" minimum <- 50 # minimum number of SSUs to be interviewed in each selected PSU # average dimension of the SSU in terms of elementary survey units #delta = nrow(pop) /length(unique(pop$id_hh)) delta = 1 # average dimension of the SSU in terms of elementary survey units deff_sugg <- 1.5 min <- 30 max <- 80 sens <- sensitivity_min_SSU ( samp_frame, errors, id_PSU, id_SSU, strata_var, target_vars, deff_var, domain_var, minimum, delta, deff_sugg, min, max) plot_sens(sens,min,max) ## End(Not run) ``` ## Author(s) Giulio Barcaroli1e:T49a,M7.49933 0.25C3.49635 0.25 0.25 3.49593 0.25 7.50024C0.25 10.703 2.32715 13.4206 5.2081 14.3797C5.57084 14.446 5.70302 14.2222 5.70302 14.0299C5.70302 13.8576 5.69679 13.4019 5.69323 12.797C3.67661 13.235 3.25112 11.825 3.25112 11.825C2.92132 10.9874 2.44599 10.7644 2.44599 10.7644C1.78773 10.3149 2.4958

plot_sens function