upDo_CoDi | R Documentation |
Convergence and divergence may be strict or weak, upward or downward. The interpretation depends on the type of indicator, that is "highBest" or "lowBest".
upDo_CoDi( myTB, timeName = "time", indiType = "highBest", time_0 = NA, time_t = NA, heter_fun = "pop_var" )
myTB |
time by member states dataset. No other variables can be in the dataset. |
timeName |
name of the variable that contains time. |
indiType |
a string, "lowBest" or "highBest". |
time_0 |
reference time. |
time_t |
target time strictly larger than time_0. |
heter_fun |
function to summarize dispersion, like var(), sd(); user-developed function are allowed; pop_var is the variance with denominator n. |
Note that if the argument heter_fun is set to sd or var, then those statistics use a denominator which is n-1, i.e. the number of observations decreased by 1. This is not typically what one wants here, thus the function pop_var may be used instead, because it adopts n as denominator. It is also possible to map a summary of dispersion with a monotonic function, like sqrt (see examples).
All the Member states contributing to the mean must be columns of the dataset given as input.
list of declarations.
# using the standard deviation upDo_CoDi(emp_20_64_MS, timeName = "time", indiType = "highBest", time_0 = 2010, time_t = 2015, heter_fun = "var" # watchout the denominator here is n-1 ) # using the standard pop_var function upDo_CoDi(emp_20_64_MS, timeName = "time", indiType = "highBest", time_0 = 2010, time_t = 2015, heter_fun = "pop_var" # the denominator here is n ) # using personalized summary of dispersion diffQQmu <- function(vettore){ (quantile(vettore,0.75)-quantile(vettore,0.25))/mean(vettore) } upDo_CoDi(emp_20_64_MS, timeName = "time", indiType = "highBest", time_0 = 2010, time_t = 2015, heter_fun = "diffQQmu" )
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