BiostatR Blog

Analyse de la sensibilité d'un automate cellulaire # Fonction qui calcule le nombre de cases occupées (=1) en fonction d'une variable X # qui est un data.frame qui contient les probabilités de mourir à chaque pas de temps (p) et  # le nombre de cases (/9) pour obtenir un décès d'étouffement. # La variable t donne les temps pour lesquels on retourne la taille de la population # Si t est une valeur, on retourne juste la valeur pour ce temps, si t est un vecteur,  # on retourne toutes les valeurs pour les temps t ac <- function(X, t=t) {   Nfinal <- NULL   for (grandtotal in 1:nrow(X)) {     penc <- X[grandtotal, 1]     v <- X[grandtotal, 2]*9     m <- matrix(data = 0, ncol=12, nrow=12)   for (i in 1:10) {     col <- sample(1:10, 1)+1     row <- sample(1:10, 1)+1     m[row, col] <- 1   }   N <- NULL   for (tps in 1:max(t)) {     m1 <- m       for (col in 2:11) {       for (row in 2:11) {         voisins <- sum(

Everyone has done a linear regression... but not everyone knows really how to do a linear regression. There are several methods which produce different outputs. Here is a little synthesis: # Let generate data. Note the the scale for x and y are different. # the set.seed(1) makes sure that the data are always the same # to make reproduced examples set.seed(1) x <- 1:10 y <- 10*x+rnorm(10, 5, 20) plot(x, y, bty="n", las=1) # First method. Only error on y axis is supposed # The square of the residuals on y axis is minimized # Why the sum of square? It is grounded on the likelihood of Gaussian distribution for residuals lm(y~ x) abline(lm(y~ x), col="red") # second, very similar to previous one, only error on x axis is supposed # The square of the residuals on x axis is minimized ir <- coef(lm(x~y)) print(c(-ir[1]/ir[2],1/ir[2])) abline(-ir[1]/ir[2],1/ir[2], col="blue") # The choice between error inputed

grib and grib2 are format used to store meteorological data. It is the native format used by ECMWF server. To read it in R with MacOSX: Using Macport, install the library wgrib2: sudo port install wgrib2 You must also install the wgrib library: Look at here: https://rda.ucar.edu/datasets/ds083.2/software/wgrib_install_guide.txt Then you can install rNOMAD package in R You must install gdal library You can use also the raster package with rgdal and goal library 4 packages can be used: rNOMAD, rgdal, raster, stars I found that the simple is to use rgdal