4
votes
4answers
194 views
+100

Texts on Various Topics in Statistics (GLMs, MCMC, Decision Trees, etc.)

I am currently looking for texts (or preferably a specific text) which have a good balance between theory and application and are as comprehensive as possible and are at an introductory level, ...
1
vote
1answer
70 views
+50

Binning method: looking for an example

I heard and read several times of the use of 'binning' methods to estimate the uncertainty and the auto-correlation time of a sample generated by MCMC but I can't find a textbook example of it being ...
6
votes
2answers
66 views
+100

The meaning of “positive dependency” as a condition to use the usual method for FDR control

Benjamini and Hochberg developed the first (and still most widely used, I think) method for controlling the false discovery rate (FDR). I want to start with a bunch of P values, each for a different ...
0
votes
0answers
71 views
+100

HoltWinters Vs ARIMA for high frequency time series

I am trying to forecast monthly time series with frequency/seasonal as 1008. Based on reading from RobjHyndman and CrossValidate it seems HoltWinters seasonal is ...
3
votes
1answer
56 views
+50

Estimating the time for completing a sequence of actions

In short: suppose I have observations for times taken to do some action. I want to estimate, how long will it take to complete a sequence of actions. The estimate should minimize the mean absolute ...
5
votes
0answers
104 views
+50

Likelihood and estimates for mixed effects Logistic regression

First let's simulate some data for a logistic regression with fixed and random parts: ...
3
votes
2answers
71 views
+50

Estimating the ratio of cell means in ANOVA under lognormal assumption

I am conducting a two-sample test (1-way ANOVA with 2 treatments), and the goal is to estimate the ratio of cell means assuming that the data are lognormal. A simple approach is to log the response ...
1
vote
0answers
79 views
+50

Estimating parameters in a two poisson process using gibbs sampling

I have the following scenario. A total of $N$ devices exists. Each device has two parts in it, call it $A$ and $B$. Each part can fail at random following a poisson model with rate parameter ...
1
vote
2answers
64 views
+50

Is there a desription in the literature of a Normal hierarchical model with hyperparameters for both the mean and the standard deviation?

I'm looking for a comprehensive description of and justification for a Normal hierarchical model where both the means of the groups and the standard deviation are modelled. It is common to find ...
1
vote
1answer
39 views
+50

Testing the variance part of a Generalized Linear Model out of sample

Suppose I have a response vector and an ANOVA design (for simplicity, assume it’s a one-way ANOVA with two treatments). A few Generalized Linear Models (Poisson, Negative Binomial, etc) are fitted to ...
1
vote
1answer
70 views
+50

Prior on a non identifiable parameter-MCMC integration

To introduce the problem I will explain the Projected normal distribution. Let $\mathbf{z}_i=(z_{i1},z_{i2})$ be a bivariate vector distributed as a bivariate normal with vector mean ...
1
vote
0answers
33 views
+50

Cross validation with nonparametric smoothing regressions

When I use regression models I like to explore functional relationships using nonparametric smoothing regression (e.g. generalized additive models, lowess, running line smoothers, etc.) before ...
0
votes
2answers
47 views
+100

Library routine for rolling window lag 1 autocorrelation?

I am looking for a library routine that will calculate the lag 1 autocorrelation of a time series with a rolling window; meaning "slide a window of size N points along the time series, calculate the ...
3
votes
0answers
36 views
+50

Linear post-treatment of nonlinear regression

I have often found in practice, using nonlinear regression techniques such as feedforward neural nets or random forests, that the resulting actual-vs-fitted plot (on training set) seems obviously ...