Cross Validated Questions, Problems & Solutions : TransWikia.com ~ Page 77

Random Censoring scheme in Weibull Distribution

I'm trying to derive the estimators of the parameters using maximum likelihood method for Weibull distribution in random censoring scheme $f(t)=alphalambda(lambda t)^{alpha -1}e^{{-lambda t}^{alpha}}$,$alpha >0$,$lambda>0$ Now i...

Asked on 12/08/2020 by Soham Bagchi

0 answer

fixed effects vs random effects vs random intercept model

This might sound a repetitive question but after reading many articles and posts online, I could never understand it entirely. I read somewhere that a random intercept model is a...

Asked on 12/08/2020 by Daniela Rodrigues

1 answer

Immediate NaN in loss function with custom activation without extreme batch size--how to prevent exploding gradients?

Using a custom activation function, when using SGD as an optimiser, except for setting the batch number to an excessively high value the loss will return as an NaN at...

Asked on 12/08/2020 by Rain

0 answer

Eacf table interpretation in R

I'm new to time series in R and have an assignment to identify the parameters for the AR and MA processes for a given time series, as well as to...

Asked on 12/08/2020

2 answer

log-odds and it's standard error as priors in logistic regression

I'm attempting to complete a Bayesian logistic regression with the outcome of whether or not a crash occurred. I have various covariates in my model that are widely used to...

Asked on 12/08/2020 by r_user

1 answer

What is the difference between $beta_1$ and $hat{beta}_1$?

Suppose I have a random sample $lbrace x_n ,y_n rbrace_{n=1}^N$. Suppose $$y_n = beta_0 + beta_1 x_n + varepsilon_n$$ and $$hat{y}_n = hat{beta}_0 +hat{beta}_1 x_n$$ What is...

Asked on 12/08/2020 by Stan Shunpike

3 answer

Interpret credible intervals / HPD following posterior sampling

I am unsure on how to interpret credible interval results. How can credible intervals consist of negative numbers when the collected data only consists of positive numbers? I would expect...

Asked on 12/08/2020 by WalterB

1 answer

Why GEE estimates are smaller than GLMM?

Both are estimators that maximize the marginal likelihood, only GLMM does so by first considering the conditional probability, while GEE assumes a covariance structure of the marginal probability directly. So...

Asked on 12/07/2020

1 answer

Help with the prior distribution

The question is as follows: Consider an SDOF mass-spring system. The value of the mass is known and is equal to 1 kg.The value of the spring stiffness is...

Asked on 12/07/2020 by Dom Jo

1 answer

Conservative confidence interval for linear combination of parameters

Consider two parameters $alpha$ and $beta$ and let $C_alpha$, $C_beta$ be their $95%$ confidence intervals, respectively. Now, take the parameter $deltaequiv f(alpha,beta)$ where ...

Asked on 12/07/2020

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