similar to: summing two probability density functions from Gompertz hazard model

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) {

Hi, all. I'm working with published paleodemographic data (counts of skeletons that have been assigned into an age-range category, based upon observed morphological characteristics). For example, the following is the age distribution from a prehistoric cemetery in Egypt: naga <-

Hi, all. I've written a function that returns the survival function for a Gompertz mortality model. I've specified the two model parameters. Using a simple integration, I can calculate the life expectancy at any age. Is there a way I can use a loop with the integration that will quickly return life expectancy over a range of ages, say 0 to 80, so that I don't have to manually type

Hello, all. I'm investigating the rate at which skeletal joint surfaces pass through a series of ordered stages (changes in morphology). Current statistical methods in this type of research use various logit or probit regression techniques (e.g., proportional odds logit/probit, forward/backward continuation ratio, or restricted/unrestricted cumulative probit). Data typically include the

Hi all, Sorry if this has been answered already, but I couldn't find it in the archives or general internet. Is it possible to implement the gompertz distribution as survreg.distribution to use with survreg of the survival library? I haven't found anything and recent attempts from my side weren't succefull so far. I know that other packages like 'eha' and

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

I haven't used r in quite a while but would like to get back into it. I have a problem that I would like to solve with r. I have some multinomial data that looks to follow an asymmetric sigmoidal growth pattern. Solving a multinomial gompertz partial differential equation in r is what I’m after. Would anyone be able to provide me the code and packages to do something like this? Regards,

Dear all! I tried to fit Gompertz growth models to describe cummulative germination rates using nls. I used the following code: germ.model<-nls(percent.germ~a*exp(-b*exp(-k*day)),data=tab,start=list(a=100,b=10,k=0.5)) My problem is that I want that the fitted model goes through the origin, since germination cannot start before the experiment was started, and y-max should be 100. Does anyone

Hi, I build a graph taking into account the times: 1, 2,4,6,8,10,12,15,18,21,24,28,32 and 48. Be that the scale of the X axis does not look right. It seems equidistant. (graph attached) What changes have I to do in the following commands so that the scale be correct? interaction.plot(Tempo, Trat, Valor, ylim=c(0, 2), las=1, lty=c(1,2,3,4), lwd=3, bty='l',

List gurus, I'm trying to code a Gompertz growth curve function as part of a larger project and have run across a problem due to my ignorance of environments. Some sample data and the function are as follows: growth <- data.frame(age = c(1.92, 3, 5.83, 3.17, 15.5, 1.17, 5.58, 13.33, 14.29, 5.83, 13.79, 6.33, 13.75, 16.83, 13, 11.67, 0.25, 1.73, 9.46, 5.67), length = c(157, 165, 179,

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

Dear all, I am fitting a parametric regression model to survival data using the flexsurvreg function from the flexsurv package. I am using a Gompertz distribution (a 2-parameter distribution) to describe the hazard function and I want to compare two groups. The model is very simple: flexsurvreg(formula = Surv(day, censored) ~ group, dist = "gompertz") and the output is also quite

Dear Sir/ Madam, I'm having trouble de-bugging the following - which works perfectly well with optim or optimx - but not with mle2. I'd be really grateful if someone could show me what is wrong. Many thanks in advance. JSC: gompertz<- function (x,t=data) { a3<-x[1] b3<-x[2] shift<-data[1] h.t<-a3*exp(b3*(t-shift))

Hello. I have yet to receive a response to my previous post, so I may have done a poor job asking the question. So, here is the general question: how can I run a run a multivariate (more than one non-independent, response variables) ordered probit regression model? I've had success doing this in the univariate case using the vglm() function in the VGAM package. For example:

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Hi- I'm a biologist trying to figure out the growth rate of salamanders in different ponds. I collected individuals from various populations at different dates, and using the size and date collected, I want to figure out the growth curve of each population. My question is: How do I fit my data to a Gompertz function in R? Thank you so much! Sarah -- View this message in context:

Dear R-users, I would like to show you a simple example that gives an overview of one of my current issue. Although my working setting implies a different parametric model (which cannot be framed in the glm), I guess that what I'll get from the following example it would help for the next steps. Anyway here it is. Firstly I simulated from a series of exposures, a series of deaths (given a

Dear all, This is a rather lengthy message, but I don't know what I made wrong in my real example since the simple code works. I have two variables a, b and a function f for which I would like to calculate all possible combinations of the values of a and b. If f is multiplication, I would simply do: a <- 1:5 b <- 1:5 outer(a,b) ## A bit more complicated is this: f <-

Dear all, This is a rather lengthy message, but I don't know what I made wrong in my real example since the simple code works. I have two variables a, b and a function f for which I would like to calculate all possible combinations of the values of a and b. If f is multiplication, I would simply do: a <- 1:5 b <- 1:5 outer(a,b) ## A bit more complicated is this: f <-