search for: makeham

...[3,] 35 50 26 [4,] 50 Inf 14 So above, the first two columns are the lower and upper limits of the age-range categories (typically used by paleodemographers), and the third column is the number of skeletons assigned to each group. I've co-opted some R script for fitting a Gompertz-Makeham hazard model to this data... ############################## GM.naga <- function(x,deaths=naga) { a2=x[1] a3=x[2] b3=x[3] shift<-15 nrow<-NROW(deaths) S.t<-function(t) { return(exp(-a2*(t-shift)+a3/b3*(1-exp(b3*(t-shift))))) } d<-S.t(deaths[1:nrow,1])-S...

I feel like a complete dolt, as I know this question has been asked by others on a fairly regular basis, but I'm going in circles trying to get the following to work: id.prob<-function (tt) { library(mvtnorm) #============================ Makeham<-function(tt) { a2=0.030386513 a3=0.006688287 b3=0.039047537 t<-tt-20 h.t<-a2+a3*exp(b3*t) S.t<-exp(-a2*t+a3/b3*(1-exp(b3*t))) return(S.t*h.t) } #=========================== trans<-function (age) { indic=c(2,2) lage=log(age) xpars=c(2.1862908,7.5528077,8.5806697,2.3319461,8.8959507,9...

...succefull so far. I know that other packages like 'eha' and 'flexsurv' offer functions similar to survreg with gompertz support. However, due to the run-time environment were this needs to be running in the end, I can't use these packages :( Same questions for the gompertz-makeham distribution. Many thanks! Matthias

Hello. I am trying to write an R function to plot the survival function (and associated hazard and density) for a Siler competing hazards model. This model is similar to the Gompertz-Makeham, with the addition of a juvenile component that includes two parameters---one that describes the initial infant mortality rate, and a negative exponential that describes typical mortality decline over the juvenile period. The entire hazard is expressed as h(x) = a1*exp(-b1*x)+a2+a3*exp(b3*x) I...

Dear list: I am attempting to use what I thought would be a pretty straightforward practical application of Cox regression. I figure users of the survival package must have come across this problem before, so I would like to ask you how you dealt with it. I have set up an illustrative example and included it at the end of this post. I took a sample of 100 data points from each of two populations

Dear All, I would like to fit some parametric survival models using left truncated, right censored data in R. However I am having problems finding a function to fit parametric survival models which can handle left truncated data. I have tested both the survreg function in package survival: fit1 <- survreg(Surv(start, stop, status) ~ X + Y + Z, data=data1) and the psm function in package

Hello, all. I have co-opted a number of functions that can be used to plot the hazard/survival functions and associated density distribution for a Gompertz mortality model, given known parameters. The Gompertz hazard model has been shown to fit relatively well to the human adult lifespan. For example, if I wanted to plot the hazard (i.e., mortality) functions: pop1 <- function (t) {