search for: lognormal

Hi, Does anyone know what the mean value of a lognormal distribution in base-2 is? I am simulating stochastic population growth and if I were working in base-e, I would do:lambda <- 1.1 #multiplicative growth rates <- 0.6 #stochasticity (std. dev)lognormal <- rlnorm(100000, log(lambda) - (s^2)/2, s)## or lognormal <- exp( rnorm( 100000, log...

Dear List, I have read that a lognormal mixture model having a pdf of the form f(x)=w1*f1(x)+(1-w1)*f2(x) fits most data sets quite well, where f1 and f2 are lognormal distributions. Any pointers on how to create a function that would produce the 5 parameters of f(x) would be greatly appreciated. > version _ platform...

...lly specified: `cauchy', `gamma', `logistic', `negative binomial' (R only, parametrized by `mu' and `size'), `t', `uniform', `weibull'. " However I cannot fit an univariate distribution named 'test' I get this: >fitdistr(test,"lognormal") Error in fitdistr(test, "lognormal") : `start' must be a named list > fitdistr(test,"lognormal",start$meanlog=0,start$sdlog=1) Error: syntax error How I am supposed to type a value for start depending on the distribution on which I am fitting my set thanks *...

Dear all, I want to compare some different models for a dataset by QQ plots and AIC. I get the following AICs: - linear model: 19759.66 - GAMLSS model: 18702.7 - linear model with lognormal response: -7862.182 The QQ plots show that the lognormal model fits better than the linear model, but still much worse than the GAMLSS. So, in my opinion, the AIC of the lognormal model should be between the AICs of the both other models. What happens here? Btw: For the lognormal model, I transfo...

...hat C_i is independent of T_i. Now, I would like to generate another random variable U_i, I = 1, 2, ..., N, which is correlated with T. In other words, I would like to generate U from the conditional distribution [U | T=t]. One approach might be to assume that the joint distn [T, U] is bivariate lognormal. So, the marginals [T] and [U], as well as the conditional [U | T] are also lognormal. I can estimate the marginal [T] using the right-censored data Y (assuming independent censoring). For example, I might use survival::survreg to do this. Then, I assume that U is standard lognormal (mean = 0,...

Dear R users I use simulated data to evaluate a model by sampling the parameters in my model from lognormal distributions. I would like these (lognormal distributed) parameters to be correlated, that is, I would like to have pairwise samples of 2 parameters with a given correlation coefficient. I have seen that a covariance matrix can be fixed when generating random variables from a multivariate norm...

...gnment on Gamma Regressions. Surfing on the web doesn't help me very much so i hope this forum may be a step forward. The question sounds as follows: The data set is in the library MASS first install library(MASS) then type data(mammals) attach(mammals) Assignment: Fit the gamma model and lognormal model for the mammals data. I appreciate any help you can provide. Best Wishes, Louisa -- View this message in context: http://r.789695.n4.nabble.com/Gamma-Lognormal-Model-tp3165408p3165408.html Sent from the R help mailing list archive at Nabble.com.

Hi, What does it mean to say Lognormal distribution with a mean of 1.03E-6 with a range factor of 100 ? How can I find the lognormal distribution paramters from this information? Thanks, Tims [[alternative HTML version deleted]]

...the subject of right censored data, but I am not sure whether or not this problem can be regarded as such. Data: I have a vector with laboratory test data (strength of wood specimens, example attached as txt-file). This data is the full sample. It is a common view that this kind of data follows a lognormal distribution. Background: When fitting a distribution to the lower tail, it will usually be very different compared to fitting the whole data. The lower tail COV is the decisive measure in my analysis (due to resistance estimations of buildings). Problem: I would like to fit a lognormal distribut...

I'm attempting to do model selection with AIC, using a glm and a lognormal distribution, but: fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian(link="log")) ## gives the same result as either of the following: fit1<-glm(BA~Year,data=pdat.sp1.65.04, family=gaussian) fit1<-lm(BA~Year,data=pdat.sp1.65.04) fit1 #Coefficients: #(Intercept) Year20...

Dear all, I'm trying to estimate the parameters of a lognormal distribution fitted from some data. The tricky thing is that my data represent the time at which I recorded certain events. However, in many cases I don't really know when the event happened. I' only know the time at which I recorded it as already happened. Therefore I want to fit the log...

Hi, I'm playing around with gamlss and don't entirely understand the sigma result from an attempted lognormal fit. In the example below, I've created lognormal data with mu=10 and sigma=2. When I try a gamlss fit, I get an estimated mu=9.947 and sigma=0.69 The mu estimate seems in the ballpark, but sigma is very low. I get similar results on repeated trials and with Normal and standard normal distri...

I am trying to plot a lognormal density curve on top of an existing histogram. Can anybody suggest a simple way to do this? Even if someone could just explain how to plot a regular normal density curve on top of an existing histogram, it would be a big help. Also, is there some way to search through the R-help archives other tha...

I am trying to fit a lognormal distribution to a set of data and test its goodness of fit with regard to predicted values. I managed to get so far: > y <- c(2,6,2,3,6,7,6,10,11,6,12,9,15,11,15,8,9,12,6,5) > library(MASS) > fitdistr(y,"lognormal",start=list(meanlog=0.1,sdlog=0.1)) meanlog sdlog...

Hi, I am trying to learn lognormal mixture models with EM. I was wondering how does one compute the log likelihood. The current implementation I have is as follows, which perform really bad in learning the mixture models. __BEGIN__ # compute probably density of lognormal. dens <- function(lambda, theta, k){ temp<-N...

Hi R Users, I'm going to estimate via. ML the parameters in Poisson Lognormal model. The model is: x | lambda ~ Poisson(lambda) lambda ~ Lognormal(a,b) Unfortunately, I haven't found a useful package allowing for such estimation. I tried to use "poilog" package, but there is no equations and it's hard to understand what exactly this package really does. U...

Full_Name: Anthony Gichangi Version: 1.90 OS: Windows XP Pro Submission from: (NULL) (130.225.131.206) The function rlnorm generates negative values for lognormal distribution. x- rlnorm(1000, meanlog = 0.6931472, sdlog = 1) Regards Anthony

...ment. Using predict() for the lm, and predict.survreg() for the survreg model and correcting for the differences in stdev, produces identical plots of the fit and the upper and lower confidence intervals. All of this is as it should be. And, vvvvvv lognormal.survreg<- survreg(formula=Surv(time=(Cycles), event) ~ log10(stress), dist="lognormal", data=survreg.df) produces summary() results that are identical to the earlier call to survreg(), except for the call, of course. The parameter estimates and SE are identical. Again this is as I w...

...95 93 86 96 113 87 112 120 71 99 [129] 99 81 96 113 85 116 112 84 120 88 97 104 99 105 153 103 92 99 99 99 90 108 104 99 105 97 94 93 99 85 91 99 [161] 118 99 91 99 103 101 102 96 99 123 85 101 88 99 93 73 97 89 94 69 74 99 97 91 92 Assuming it follows a lognormal distribution I'd like to determine the mean and the sd thanks to maximum likelihood estimation > fitdistr(test,"lognormal",start=list(200,10)) Error in print.fitdistr(structure(list(estimate = c(4.54666263736726, : more elements supplied than there are to replace I chose...

I'm trying to produce empirical bayes estimates based on the lognormal model in disease mapping Is there a way this can be done in R? thanks Oarabile