Linked Questions

2
votes
1answer
277 views

How to fit gamma distribution to events not happen? [duplicate]

I am trying to fit a gamma distribution to the failure time of a kind of bulb. I have 40 data. However only half of them are actually the failure time. The result 20 are times those bulbs being used (...
0
votes
0answers
76 views

Likelihood formulation in linear regression with right censored data [duplicate]

I want to formulate the likelihood function in a linear regression problem in which I have censored observations. Considering the dataset $(x_i,y_i)$, I suppose that the dependent variable is normally ...
36
votes
2answers
12k views

Confidence interval around binomial estimate of 0 or 1

What is the best technique to calculate a confidence interval of a binomial experiment, if your estimate is that $p=0$ (or similarly $p=1$) and sample size is relatively small, for example $n=25$?
4
votes
0answers
619 views

How is maximum likelihood estimation method defined for non-continuous and non-discrete distributions? [duplicate]

Consider a task of estimating a parameter of a censored exponential distribution using maximum likelihood estimation. The typical approach to this question is presented in this question. The linked ...
0
votes
0answers
530 views

Maximum likelihood of gaussian with right censoring

I'm trying to fit the mean $\mu$ of right-censored gaussian data ($n$ samples) in a toy example (let's assume $\sigma^2=1$ is known), and the censoring happens always at the same value $s$. As far as ...
3
votes
1answer
369 views

Estimating a rate of failure/survival using only right censored data?

I am trying to estimate the probability $q$ that a household with certain known covariates will move to a new home in the following year, by estimating an event rate $\lambda$ dependending on some ...
0
votes
0answers
354 views

Estimate parameters from truncated normal sample [duplicate]

I have a question like this, $X \sim N(\mu,\sigma^2)$ with unknown parameters. Now, a sample of size $m$ generated from X, but filter by X < T, i.e., any number larger than T will be ignored and ...
2
votes
1answer
186 views

truncated binomial samples with GLM

We have a binomial process that yields samples of 60 trials. To save time, once 2 failures have been observed the process is reset. So if a test series hits 2 failures early, the resultant sample ...
0
votes
2answers
166 views

Intuitive explanation of censored data in a Cox model

I use Cox regression (proportional hazards) to model survival for a cohort of patients. Patients are censored (alive (0), dead (1)). I was wondering how Cox regression uses censored data intuitively. ...
4
votes
1answer
87 views

How to fit a distribution with an “10 and more” category at the bottom?

I want to fit a distribution to some data to sample from it in a subsequent simulation. There are I got a dataset that looks somehwat like this: ...
2
votes
0answers
68 views

Maximum likelihood estimator with atoms

MLE (maximum likelihood estimation) can be defined mathematically for discrete or continuous variables. But there is a technical specificity about variables being neither discrete nor continuous. ...
1
vote
1answer
21 views

Null Target Variable

I am trying to predict - Number of days it takes for a customer to make the second purchase. Sometimes the customer comes back in 2,5,6,10.... days and sometimes the customer does not come back which ...