kols: Dataset with data from the COPD health atlas
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Helseatlas/helseatlas: R-package to produce shiny maps of Norway
R: Dataset with data from the COPD health atlas
kolsR Documentation
Dataset
R: Dataset with data from the COPD health atlas
kolsR Documentation
Dataset
R: Map from the COPD healthcare atlas
kolsR Documentation
Map from the COPD
R: Dataset with data from the COPD health atlas
kolsR Documentation
Dataset
R: Map from the COPD healthcare atlas
kolsR Documentation
Map from the COPD
R: Dataset with data from the COPD healthcare atlas
kolsR Documentation
R: Plot a KOL team in a network
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function
R: Statistical data analysis support functions Sergey "kol"...
remove_outliersR Documentation
Statistical data
#' Plot a KOL team in a network
#'
#' @param KOL a KOL object generated by \code{pick_kols()}
goal
string: goal for the KOL team (either "diffusion" or "adoption")
integer: KOL team centrality parameter (m
x = readr::read_csv("countries_list.csv")
kol = ItalyCovid19::create_adjacency_matrix(x$alpha3, x$lat, x$long)
diag, lesid) {
## dt - Dataset
## code - From codebook(),'colorlist.pdf')
pdf(dstpdf,width=14.57, height=8.2, onefile=TRUE)
kol <- colors()
= mean(lat))
# Create adjacency matrix
kol = ItalyCovid19::create_adjacency_matrix(x1$denominazione_provincia, x1$Lat
<-as.matrix(Startmatris,col=2)
colnames(Startmatris_1) <- c("N0_K","N0_M")
Kol<-NCOL(assumptions)-1
Startmatris_1<-as.matrix(Startmatris,col=2)
colnames(Startmatris_1) <- c("N0_K","N0_M")
Kol<-NCOL(assumptions
) %>%
summarise(Long = mean(long), Lat = mean(lat))
# Create adjacency matrix
of information
#' @param goal string: goal for the KOL team (either \code{"diffusion"} or \code{"adoption"})
#' @param m integer: KOL
--------------
is_delete_lesid <- function(dt, code, lesid){
LESID <- KOL <- FRA <- NULL
, ' FROM ', exportModelTable,' where MODELUSAGE= \'Column Statistics\'',sep="")
kols <- idaQuery(model4
= \'Column Statistics\'',sep="")
kols <- idaQuery(model4)
}, error = function(e) {
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