search for: alfa1

...ng to find the parameters of one likelihood function, but when i otimize it, always appers a error or advertisement and the solve does not occur. The problem seems like that: "lMix<-function(pars,y){ beta1<-pars[1] beta2<-pars[2] beta3<-pars[3] beta4<-pars[4] beta5<-pars[5] alfa1<-pars[6] Fsp<-log(1/(1+exp(beta1*y[,10]+beta2*y[,3]+beta3*y[,3]+beta4*y[,5]+beta5*y[,6]+alfa1*y[,11]))) Frp<-log(1/(1+exp(beta1*y[,10]+beta2*y[,3]+beta3*y[,3]+beta4*y[,5]+beta5*y[,6]))) logl<- sum((y[,15]*Fsp)+(y[,19]*Frp)) return(-logl) } optim(c(1,1,1,1,1,1), llMix, y=Mix, method=&quo...

...share/freeling/config/es.cfg --lang es --outf tagged </Users/earlbrown/temp_input.txt' had status 139 and sometimes I receive a "Trace/BPT trap: 5" error: dyld: lazy symbol binding failed: Symbol not found: __ZN6icu_496LocaleD1Ev Referenced from: /usr/local/lib/libfreeling-3.1-alfa1.dylib Expected in: flat namespace dyld: Symbol not found: __ZN6icu_496LocaleD1Ev Referenced from: /usr/local/lib/libfreeling-3.1-alfa1.dylib Expected in: flat namespace /usr/local/bin/analyze: line 39: 2864 Trace/BPT trap: 5 $FREELING/bin/analyzer $param Warning message: running comm...

...rror Si Tj conocidos: Y = M + ?(betaj*X1j + gammaj * X2j) + error Modelado: y ~ x1tot+ x2tot, donde los xtot (x totales) resultan de la suma de los parciales (donde cada parcial corresponde a un Tj). Sin embargo, en el caso del modelo generalizado (componente cuadrática, cúbica, etc.): Y = M + alfa1*t + alfa2*t2 + (?Aj * cos(2*pi*t/Tj + phij)) + error ¿Qué facilidades ofrece R para el estudio de este modelo?. Se hace manualmente?. Gracias. Un saludo.

...ed Log-Likelihood function for the Weibull regression model # (see reference 1 in help file) # # Note: negative Log-likelihood value is returned # to facilitate finding of extreme value of ELL in # find.mu.alfa # np <- length(theta) - 2 alfa <- theta[np + 2] mu <- theta[np + 1] alfa1 <- theta1[np + 2] mu1 <- theta1[np + 1] beta <- theta[1:np] beta1 <- theta1[1:np] a <- alfa/alfa1 b.beta <- t(as.matrix(beta - a * beta1)) %*% t(x) b <- (mu - a * mu1) + b.beta ga1 <- gamma(a + 1) # # negative value of ELL is returned ! # - (log(alfa) - 0.5772...