I'm new to using pymc3, I've read Bayesian Methods for Hackers and done my best to work through existing survival analysis tutorials in pymc3. However, I don't understand how to write/interpret the...

I'm trying to build a survival model in JAGS that allows for time-varying covariates. I'd like it to be a parametric model — for example, assuming survival follows the Weibull distribution (but I'd...

I am trying to recreate maximum likelihood distribution fitting, I can already do this in Matlab and R, but now I want to use scipy. In particular, I would like to estimate the Weibull distribution...

I’m trying to fit and plot a Weibull model to a survival data. The data has just one covariate, cohort, which runs from 2006 to 2010. So, any ideas on what to add to the two lines of code that foll...

I have been doing some data analysis in R and I am trying to figure out how to fit my data to a 3 parameter Weibull distribution. I found how to do it with a 2 parameter Weibull but have come up sh...

I was wondering how to generate a random weibull distribution with 2-parameter (lambda, k) in python. I know that numpy has a numpy.random.weibull, but it only accepts the a parameter as the shape ...

I need to estimate the shape and scale parameters of a Weibull distribution from a sample data using MLE. I checked the WeibullDistribution class of Apache commons Math but it doesn't have such fun...

I have a data which is the interval days of customers purchasing products. I try to estimate the shape and scale params by scipy.stat.weibull_min But, the parameters returned from the fit functio...

I have a dataset that I would like to fit to a known probability distribution. The intention is to use the fitted PDF in a data generator - such that I can sample data from the known (fitted) PDF. ...

I would like to identify the Weibull parameters (i.e. the shape and scale) of my data. 0.022988506 0.114942529 0.218390805 0.114942529 0.149425287 0.114942529 0.068965517 0.068965517 0.034482759...

I have frequency values changing with the time (x axis units), as presented on the picture below. After some normalization these values may be seen as data points of a density function for some dis...

I am building an R package to display Weibull plots (using graphics::plot) in R. The plot has a log-transformed x-axis and a Weibull-transformed y-axis (for lack of a better description). The two-p...

I would like to estimate power of the following problem. I am interested in comparing two groups that both follow Weibull distribution. So, group A has two parameters (shape par = a1,scale par = b1...

Here is my data: https://www.dropbox.com/s/xx02015pbr484es/Book2.xlsx This is my output: And this is the desired output: As you can see,I want "the data" and the "Weibull distribution" ...

Suppose I have an array: adata=array([0.5, 1.,2.,3.,6.,10.]) and I want to calculate log likelihood of Weibull distribution of this array, given the parameters [5.,1.5] and [5.1,1.6]. I have never ...

I am trying to model some data that follows a sigmoid curve relationship. In my field of work (psychophysics), a Weibull function is usually used to model such relationships, rather than probit. I...

I have the following survreg model: Call: survreg(formula = Surv(time = (ev.time), event = ev) ~ age, data = my.data, dist = "weib") Value Std. Error z p (Intercept) 4.0961 0.5566 7.36 1.86e-1...

I am trying to generate an inverse Weibull distribution using parameters estimated from survreg in R. By this I mean I would like to, for a given probability (which will be a random number in a sma...