search for: coefficientes

...2,2.3,2.4, 2.3,2.4,2.6,2.6, 2.5,2.6,2.9,3, 2.6,NA,3.2,4) a <- matrix(a, nr=4) aa <- as.data.frame(a) names(aa) <- c("ID","X1","X2","X3","X4","Y1","Y2","Y3","Y4") # # I want the regression coefficientes of the Y on the X for each ID # sl <- rep(NA,4) for(i in 1:4) { x1 <- a[i,2:5] y1 <- a[i,6:9] sl[i] <- lm(y1 ~ x1)$coef[2] } sl # # I would like to use apply on the data.frame aa but with which function? # sl <- apply(aa,1,FUN) # FUN = ?? # Thanks for any help R.Heberto Ghez...

Why the standadard errors of the coefficientes of the arma models fited by using the arima procedure in the stats package doesnt coincide with that of S+, minitab or SAS? -- Este mensaje ha sido analizado por MailScanner en busca de virus y otros contenidos peligrosos, y se considera que est? limpio.

...ter several tries, I got this model log(tle) = sexcolor + s(doy, bs = "cc", by = sexcolor) +log(tl) sexcolor is a factor with 4 levels doy is "day of year", which is modeled as a smoother tl is "total length of the fish" The summary of this models is (only parametric coefficientes): Parametric coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.34237 0.42340 -3.170 0.001733 ** sexcolorSpotted males -0.04405 0.12568 -0.350 0.726309 sexcolorPlai...

Hi, I am running a model with count data and one categorical predictor (simple model for me to understand it fully), I did in R a glm like this: glm(Recruitment~Depth, family=poisson). I get the coefficientes and confidence intervals and all is ok. But then I want to do the same model with Bayesian stats, here is my code: model { for (i in 1:232) { Recruitment[i]~dpois(lambda[i]) log(lambda[i])<-a+b[Depth[i]]*Depth[i] } a~dnorm(0,0.000001) b[1]~dnorm(0,0.000001) b[2]~dnorm(0,0.000001) b[3]~dnorm(0,0...

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