search for: n_length

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2002 Apr 22
3
glm() function not finding the maximum
...2.45, 58.16, 176.58, 76.58, 434.12, 362.35, 102.53, 103.6, 25.23, 97.19, 88.52, 118.55, 151.9, 2.7, 156.41, 21.79, 272.27, 23.16, 32.07, 6325.23, 92.37, 8340.04, 51.08, 55.59, 94.08, 69.98, 554.13, 104.88, 170.15, 945.1, 143.52) #Fits data to a gamma distribution using glm() gamma1_function(data){ n_length(data) m_summary(glm(data~1, family=Gamma(link=identity))) shape_1/as.numeric(m$disp) scale_as.numeric(m$coeff[1]*m$disp) dev.res_-2*log(dgamma(data,shape=shape,scale=scale)) loglik_sum(dev.res) #actually -2 * log like list(loglik=loglik,par=c(shape,scale)) } #Fits data to a gamma distribution &...
2002 Jun 07
2
Hope fo help - functions, fits and for cycles
...,1.5) dataset<-data.frame(ID,gender,age,G1,G2,G3,response) GG<-c("G1","G2","G3") # here I construct a function that makes a basic fit, then updates with each variable from GG vector. trial_function(mydata,formule,expl,distr="binomial") { n_length(expl) fit.low_glm(formule, family = distr, data = mydata, na.action = na.exclude) for (j in 1:n) { fit_update(fit.low,~.+ mydata[,expl[j]]) print(mydata[,expl[j]]) } } result<- trial(mydata=dataset,formule=response~gender+age,exp l=GG,distr="gaussia...
1999 Oct 21
1
left.solve
...if (ares) { plot(rslt$fit, rslt$res) abline(h=0,lty=2) if (!is.null(f)) lines(lowess(rslt$fit,rslt$res, f=f)) } else { plot(x, y, xlab=xlab, ylab=ylab, cex=cex) if (!is.null(f)) lines(lowess(x,y,f=f)) } } else { lms_summary(rslt) e_rslt$residuals n_length(e) beta_rslt$coef p_length(rslt$coef) R_rslt$R Q_left.solve(R, cbind(rep(1,length(x)),x)) h_as.vector((Q^2 %*% array(1, c(p, 1)))) h.res_(1 - h) z_e/h.res v1_e^2 z_t(Q * z) v.res_sum(v1) v1_(v.res - v1/h.res)/(n-p-1) dbeta_backsolve(R, z) si_sqrt(...