search for: valideta

...lt;- qlogis( (mu - POD.floor)/(POD.ceiling - POD.floor) ) } linkinv <- function(eta) { eta <- POD.floor + (POD.ceiling - POD.floor)*plogis(eta) } mu.eta <- function(eta) { (POD.ceiling - POD.floor)*dlogis(eta)# derivitaive of mu with respect to eta } valideta <- function(eta) TRUE link <- paste("logit.FC(", POD.floor, ",", POD.ceiling, ")", sep = "") structure(list(linkfun = linkfun, linkinv = linkinv, mu.eta = mu.eta, valideta = valideta, name = link), class = "link-glm") } as...

...: logical function. Returns ?TRUE? if a mean vector ?mu? is within the domain of ?variance?. valid.eta: logical function. Returns ?TRUE? if a linear predictor ?eta? is within the domain of ?linkinv?. However, the real names of these elements are "validmu" and "valideta" (no dots); try names(poisson()) or names(binomial()) and see ... Can someone on R-core fix this and save me the trouble of filing a bug report ... ? Or have I misunderstood something? cheers Ben Bolker

Dear all I am using NAMESPACE in my package but I would like the user to be able to overwrite four functions: own.linkfun, own.linkinv, own.mu.eta and own.valideta. These are used to defined "own" link functions. Is there any way of doing that without getting the when I am checking the package? This is what I am getting: make.link.gamlss : linkfun: no visible binding for global variable 'own.linkfun' make.link.gamlss : linkinv: no visi...

...;- family$variance 22 dev.resids <- family$dev.resids 23 aic <- family$aic 24 linkinv <- family$linkinv 25 mu.eta <- family$mu.eta 26 if (!is.function(variance) || !is.function(linkinv)) 27 stop("illegal `family' argument") 28 valideta <- family$valideta 29 if (is.null(valideta)) 30 valideta <- function(eta) TRUE 31 validmu <- family$validmu 32 if (is.null(validmu)) 33 validmu <- function(mu) TRUE 34 if (is.null(mustart)) { 35 eval(family$initialize) 36 }...

...;s glm routine does not supply the "loglog" link. I modified the make.link function adding the code: }, loglog = { linkfun <- function(mu) -log(-log(mu)) linkinv <- function(eta) exp(-exp(-eta)) mu.eta <- function(eta) exp(-exp(-eta)-eta) valideta <- function(eta) all(eta != 0) }, stop(sQuote(link), " link not recognised")) structure(list(linkfun = linkfun, linkinv = linkinv, mu.eta = mu.eta, valideta = valideta, name = link), class = "link-glm") } and then call glm with argument glm(y~x1+x2+x3,fa...

...the link function I use: logexp <- function(days = 1) { linkfun <- function(mu) qlogis(mu^(1/days)) linkinv <- function(eta) plogis(eta)^days mu.eta <- function(eta) days*.Call("logit_mu_eta", eta, PACKAGE = "stats")*plogis(eta)^(days-1) valideta <- function(eta) TRUE link <- paste("logexp(", days, ")", sep="") structure(list(linkfun = linkfun, linkinv = linkinv, mu.eta = mu.eta, valideta = valideta, name = link), class = "link-glm") } # Modified binomial family function...

...eta/2)+exp(-eta/2))^-2 half.logit.inv.indicator=function(eta) TRUE half.logit.indicator=function(mu) mu>.5 & mu<1 link <- "half.logit" structure(list(linkfun = half.logit, linkinv = half.logit.inv, ??????????????????? mu.eta = half.logit.deriv, validmu = half.logit.indicator ,valideta = half.logit.inv.indicator, name = link), ?????????????? class = "link-glm") } # submit halflogit function to lmer rcNrPSrcNxPSxP<-lmer(Correct~-1+cNoise*f_Pos+f_Shape_con+f_Shape_con:f_Pos+(-1+cNoise*f_Pos|f_Subject), data=dens_data, family=binomial(halflogit())) #resulting error mes...

...s the custom link function: logexp <- function(days = 1) { linkfun <- function(mu) qlogis(mu^(1/days)) linkinv <- function(eta) plogis(eta)^days mu.eta <- function(eta) days * plogis(eta)^(days-1) * .Call("logit_mu_eta", eta, PACKAGE = "stats") valideta <- function(eta) TRUE link <- paste("logexp(", days, ")", sep="") structure(list(linkfun = linkfun, linkinv = linkinv, mu.eta = mu.eta, valideta = valideta, name = link), class = "link-glm") } Thanks in advance...

...##Custom link function from Shaffer (2004) Auk 121:526-540. { linkfun <- function(mu) qlogis(mu^(1/days)) linkinv <- function(eta) plogis(eta)^days mu.eta <- function(eta) days * plogis(eta)^(days-1) * .Call("logit_mu_eta", eta, PACKAGE = "stats") valideta <- function(eta) TRUE link <- paste("logexp(", days, ")", sep="") structure(list(linkfun = linkfun, linkinv = linkinv, mu.eta = mu.eta, valideta = valideta, name = link), class = "link-glm") } model0 <- glm(s...

...- pmax(.Machine$double.eps, eta^(1/lambda)) + pmax(eta^(1/lambda), .Machine$double.eps) mu.eta <- function(eta) - pmax(.Machine$double.eps, (1/lambda) * eta^(1/lambda - 1)) + pmax((1/lambda) * eta^(1/lambda - 1), .Machine$double.eps) valideta <- function(eta) all(eta>0) } else @@ -36,7 +36,7 @@ linkfun <- function(mu) log(mu/(1 - mu)) linkinv <- function(eta) { thresh <- -log(.Machine$double.eps) - eta <- pmin(thresh, pmax(e...

...function(y, n, mu, wt, dev) NA structure(list(family = "quasi", link = linktemp, linkfun = stats$linkfun, linkinv = stats$linkinv, variance = variance, dev.resids = dev.resids, aic = aic, mu.eta = stats$mu.eta, initialize = initialize, validmu = validmu, valideta = stats$valideta, varfun = variancetemp), class = "family") }

I would like to do an R glm() with family = binomial(link="loglog") Right now, the cloglog link exists, which is nice when the data have a heavy tail to the left. I have the opposite case and the loglog link is what I need. Can someone suggest how to add the loglog link onto glm()? It would be lovely to have it there by default, and it certainly makes sense to have the two opposite

...ta/2)+exp(-eta/2))^-2 half.logit.inv.indicator=function(eta) TRUE half.logit.indicator=function(mu) mu>.5 & mu<1 link <- "half.logit" structure(list(linkfun = half.logit, linkinv = half.logit.inv, mu.eta = half.logit.deriv, validmu = half.logit.indicator ,valideta = half.logit.inv.indicator, name = link), class = "link-glm") } binomial(halflogit()) Family: binomial Link function: half.logit ############################# I based this off the help for the family() function. So I try to call glmmPQL (based on other R-help posts, thi...

...un <- function(mu) qt(mu,nu) linkinv <- function(eta) { thresh <- -qqt(.Machine$double.eps,nu) eta <- pmin(thresh, pmax(eta, -thresh)) pt(eta,nu) } mu.eta <- function(eta) pmax(dt(eta,nu), .Machine$double.eps) valideta <- function(eta) TRUE }, Just prior to the useR meeting, there were some changes in R-devel to binomial that allow one to pass an object of class "link-glm" -- if I understand properly, this allows one to more easily roll one's own links, but it leaves the question of passing...

...features, for example: In R: > names(Gamma()) [1] "family" "link" "linkfun" "linkinv" "variance" [6] "dev.resids" "aic" "mu.eta" "initialize" "validmu" [11] "valideta" In S-Plus: > names(Gamma()) [1] "family" "names" "link" "inverse" "deriv" [6] "initialize" "variance" "deviance" "weight" > My question concerns the variable weight in...

Dear R users I have been looking for functions that can deal with overdispersed poisson models. Some (one) of the observations are negative. According to actuarial literature (England & Verall, Stochastic Claims Reserving in General Insurance , Institute of Actiuaries 2002) this can be handled through the use of quasi likelihoods instead of normal likelihoods. The presence of negatives is not

I apologize for my earlier posting that, unbeknownst to me before, apparently was not in the correct format for this list. Hopefully this attempt will go through, and no-one will hold the newbie mistake against me. I could really use some help in writing a new glm link function in order to run an analysis of daily nest survival rates. I've struggled with this for weeks now, and can at least

Hi to every body. I would like assistance on how to implement the log-log link function for binary response. Is there any package that implements it? Many thanks Endy [[alternative HTML version deleted]]

Dear list, I have recently encountered an odd error when running glm(dep~indep, quasipoisson): while, with a subset of my data, I could get a perfectly reasonable model, once I include all of my data (17K+ observations, 29 variables), I get the following error: Error in if (any(y < 0)) stop("negative values not allowed for the quasiPoisson family") : missing value where

This is not so much a bug as an infelicity in the code that can easily be fixed. The initialize expression in the quasi family function is, (uniformly for all links and all variance functions): initialize <- expression({ n <- rep.int(1, nobs) mustart <- y + 0.1 * (y == 0) }) This is inappropriate (and often fails) for variance function "mu(1-mu)".