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In R, different point estimates of odds ratio from fisher.test() and manual calcuation

In R, I have two different odds ratios from fisher.test() and manual calculation. I do not understand how fisher.test() calculates such odds ratio. Could someone explain it? Also, could you tell me ...
  • 101
2 votes
1 answer
16 views

Formal Definition of Identification

This definition of identification (the bracketed part) is confusing to me because (based on my obvious misunderstanding) it fails for probit: Probit with 2 covariates: $f=\Theta(X_1\theta_1+X_2\...
2 votes
1 answer
22 views

When does R-squared in multiple linear regression equals the sum of the R-squared from two simple linear regression?

I know that in the simple linear regression, the $R^2$ is just the sample correlation between the response and covariate. My question is that suppose I fit a linear regression by using two covariates, ...
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0 votes
0 answers
9 views

Calculating expected utiity utilising integrate in R

In short, I need some help calculating some expected utility using the integrate function in R, but first I will present some background to my problem. In order to predict whether a product is ...
  • 1
0 votes
0 answers
5 views

Use covariate from original article in correlational meta-analysis?

I am conducting a correlational meta-analysis with r as the data. I've found lots of articles that aren't looking at my association of interest primarily (let's say X and Y), but include one or both ...
  • 1
0 votes
1 answer
16 views

Bayesian Posterior distribution for binomial distribution with uniform prior

Suppose we have two independent binomial distribution given p, i.e. $X_1|p \sim Bin(n_1, p)$, $X_2|p \sim Bin(n_2, p)$. We also know the prior distribution for p is $p \sim U(0,1)$. Now I would like ...
  • 111
0 votes
0 answers
6 views

Transforming Dependent Joint Distribution into Independent Joint Distribution

Hi please help me with this problem. I also posted this question in the other community so feel free to answer on one of the sites. With the random samples $X_1,...,X_n$ from $Exp(\mu, \sigma)$, I ...
3 votes
1 answer
38 views

What estimation methods other than ordinary least squares guarantee the orthogonality of predictions and residuals?

From my question here, it is evident that estimation approaches to linear regression other than ordinary least squares can result in the predictions and residuals lacking orthogonality, despite the ...
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0 votes
0 answers
4 views

Why do unknown objects that are close destroy the reconstruction error of my Autoencoder?

I built up a convolutional Autoencoder and trained it on a large set of synthetic streets, that do not contain any other vehicles or objects within the roads. The quality of my reconstructions (image ...
0 votes
0 answers
9 views

If residuals are serially correlated does that mean they are normally distributed

In linear regression if the residuals are serially correlated does that mean then that they are normally distributed
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0 votes
0 answers
7 views

Why should the weight matrix encode word embeddings in CBOW/skip-gram?

Sorry for the beginner level question, but I am fairly new to the NLP world and am trying to better understand how word2vec is able to create useful word embeddings. I'm looking for an intuitive ...
0 votes
0 answers
6 views

Risk bound of soft thresholding estimator

I am trying to find risk bound of soft threshold for univariate, attached in this figure. 1:
1 vote
1 answer
14 views

Correction for multiple comparisons using sum contrasts with linear regression

I am computing the following model using the lme4 package in R: ...
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0 votes
0 answers
29 views

Statistical Analysis for Physics Research Project

Important concepts for Problem: $\chi^2$ test, $p$-value, $\sigma$ Significance I am an undergraduate Physics student working on a research project which involves a certain level of statistical ...
1 vote
1 answer
19 views

Constructing a confidence interval using the asymptotic approach

Consider a random pair of scalars $(x; y)$ for which a random sample $\{(x_i; y_i)\}^n_{i=1}$ is available. Denote $g(x) = E [y|x]$ the conditional mean. Suppose we are interested in constructing a ...
0 votes
0 answers
13 views

Variance of an Estimator of a function [closed]

So I have a question regarding the variance of an Estimator of a function of X, and what then happens when $n \to \infty$. More clearly I have the RV $X$, and I wan't to find the expected value of the ...
0 votes
0 answers
12 views

Is the lack of independent variables a problem in a fixed effects regression?

I am currently working on a research project for my Master's degree. I use panel data at the country-month level but I have a problem of data availability regarding my topic, because besides my ...
0 votes
0 answers
18 views

"Random" effects from "fixed" variables (in logistic regression)?

I've been getting a bit lost in translation when it comes to the term "random" in "random effects" and "random sampling". I found a lot of useful posts on how to define a ...
  • 777
0 votes
1 answer
23 views

How to calculate variance of AR(1) process

I have a stationary AR(1) process: $Z_t = \alpha_{1}Z_{t-1} + \nu_{t}$, where $\nu_t$ is white noise and $|\alpha_1| < 1$. I have to show that the variance of $\Delta Z_t$ is $$V[\Delta Z_t] = 2\...
0 votes
2 answers
14 views

Why does X @ coef_ + intercept_ does not equal Y_pred for sklearn PLSRegression?

I performed partial least squares regression using Python's sklearn.cross_decomposition.PLSRegression using the example data in the sklearn docs. I am surprised that X @ coef_ + intercept_ does not ...
1 vote
1 answer
22 views

When is there enough or too much balancing in observational causal studies?

I'm trying to compare exam performance across genders when I match on a variety of students' characteristics (e.g., their age, parental income etc). I have many such matchable variables. My question: ...
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0 votes
0 answers
10 views

How to specify a VAR model in R with non-stationary, stationary, and trend-stationary variables?

I have a multivariate time series and I want to estimate a VAR model. I tested for unit roots with the ADF and KPSS test and concluded that some variables are non-stationary, while others are ...
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1 vote
2 answers
16 views

What distribution should I use to model bounded count data (that also feels a bit like a proportion)?

I am trying to determine the correct model for my data. I want to model the effect of two categorical independent variables (and their interaction) on my outcome variable. I am using SAS (proc genmod, ...
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0 votes
0 answers
4 views

Why same t-score for contrast pairs involve continuous x continuous interaction (emtrends)?

I want to calculate the difference in simple slope estimates for two-way interactions that involve two continuous variables. But I found the t-score is all the same for the contrast-pair results when ...
-2 votes
0 answers
16 views

regression plots for each group separately [closed]

I want to plot regression lines for each group separately. Each group's regression plot as 1 plot. I have around 100 groups. So it will be 100 plots. Can this be done automatically without selecting ...
  • 1
0 votes
0 answers
10 views

Calculate mean and quartiles for exponential distribution, which consists of a sum of two E-functions [closed]

How to calculate the mean, quartiles and variance for an exponential distribution with the following function: 17/99 e^(-0.5y) + 82/99 e^(-0,25y)
1 vote
2 answers
22 views

RMSE loss tends to output the same prediction

When using MSE (or RMSE) loss for regression tasks in deep learning my models usually output the same result for each record. My guess is that the models are "playing safe" and they output a ...
2 votes
1 answer
35 views

Causal Diagram and multiple regression

I have 4 nodes: A causes B and C, and C by itself causes D. However, C is not measurable, and my interest is to test the association between B and D. What would be the right causal diagram and ...
0 votes
0 answers
13 views

Can anyone provide me with reference to some lecture notes or an online lecture on Multiplicative Error Models?

As the title says, I am looking for some lecture notes or an online class going over Multiplicative Error Models. I have found a number of academic papers on the topic, but I am having trouble ...
0 votes
0 answers
11 views

building design matrix of random effects in a LMM

I am working in simulations of data following a LMM. The general formula of the model, as defined in most texts books is as follows: $$Y=X\beta+Zb+\epsilon$$ Where $b\sim N(0,D)$, $\epsilon \sim N(0,R)...
0 votes
0 answers
3 views

off-policy Monte Carlo learning: Why is Probability of Sampling a Trajectory the same as Having a return?

In Sutton and Barto's RL book, in the section for off-policy learning, we would like to find the expected value of the random variable $G_t$, given $S_t = s$ under our target policy: $$E_{\pi}[G_t|S_t ...
1 vote
0 answers
11 views

Kinds of Expectation-Maximization [closed]

I'm starting to dig into the variational inference literature, as I need to solve a learning problem where the latent variables form an hierarchical structure (an hierarchical Gaussian generative ...
  • 315
5 votes
3 answers
89 views

Introductory material on splines

I am looking for a basic, step-by-step introduction into modelling with splines. (I have encountered splines while teaching another topic. The textbook I am using does not cover splines in sufficient ...
0 votes
0 answers
6 views

Hoe calculate the conditional probabilities for t test?

Suppose that I obtain a number D from my research. The null hypothesis $H_0$ says that D is a sample from a normal distribution with mean 0 and standard deviation 1. The alternative hypothesis $H_1$ ...
  • 101
0 votes
0 answers
13 views

What is the correct method to compare linear mixed models and select the best one?

Suppose we have four variables, say, x, y, z and w, and we are fitting a linear mixed effects model with x as the target and y ...
0 votes
0 answers
4 views

Factorial non-discrete HMM model and fitting

I've been using hmmlearn (https://github.com/hmmlearn/hmmlearn) to extract the states from some data (current measurements with RTN jumps due to trapped electrons in the gate). The current (from ...
0 votes
1 answer
16 views

Implementing cross-validation to tune the hyperparameters of an unsupervised model

I have extensively researched the application of cross validation for unsupervised learning (as it is a requirement by my project manager) but it seems that there is no clear consensus as to how to ...
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0 votes
0 answers
6 views

How to maximize the ELBO in coordinate ascent variational inference

In the lecture by D.Blei: https://www.cs.princeton.edu/courses/archive/fall11/cos597C/lectures/variational-inference-i.pdf Variational inference is explained and he shows how to derive the optimal ...
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0 votes
1 answer
11 views

What should the dimension of the mean and variances vectors in the VAE decoder be?

According to "Autoencoding Variational Bayes" article by Kingma and Welling the decoder part of the VAE should roughly look like this: ...
  • 115
0 votes
0 answers
5 views

Space Complexity Reduction for Dynamic Time Warping

I'm currently trying to use dynamic time warping to group a large number of time-series I have. Unfortunately, each series has around 400000 entries, and Python can't handle creating a 400000 x 400000 ...
2 votes
2 answers
60 views

Maximum likelihood estimator of $p$ for the binomial (truncated) distribution

This question is from the book "Introduction To The Theory Of Statistics, Mood Alexander", Chapter 7, Problem 15. In genetic investigations one frequently samples from a binomial ...
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0 votes
0 answers
6 views

Marginal mean distribution with Gaussian Process

The marginal posterior over the mean for normally distributed data with a known variance $\sigma^2$ is (from here) normally distributed, with parameters: $$ \mu' = \frac1{\frac1{\sigma^2_0} + \frac{n}{...
  • 101
1 vote
0 answers
23 views

NLP as a Poisson Regression Problem?

Suppose I encode the sequence to sequence dataset as a vector of integer $\{0,1\cdots N\}$ where $N$ is the maximun number of unique words in the dataset. For example, I am planning to build a chatbot ...
  • 497
0 votes
0 answers
4 views

statistical test to distinguish groups effected by treatment

I have a set of 395 data points that are classified to 90 groups whose sizes range (1-30). For each data point I have two measurements taken in two different conditions - one being the control and one ...
0 votes
0 answers
12 views

How I can choose best regression model on my data? [closed]

[I want to find the best fit curve or model for my data and my data follows the following pattern. I have tried the curve fitting tool on Matlab but no model fits precisely on the data. Could you ...
  • 1
1 vote
1 answer
20 views

The correct treatment of censorship and observation periods in survival analysis using longitudinal observational data

I have longitudinal retrospective data and want to perform Cox proportional hazards regression. Still, I would be extremely grateful if the CrossValidated community could sanity-check my understanding ...
0 votes
2 answers
26 views

Using several train/test split ratios

This is probably a more theoretical question than a practical one. Recently I've been asked to provide the performance of a Machine Learning pipeline under different train/test ratios. To me, this ...
0 votes
0 answers
14 views

Using Principal Component Analysis on variables de-trended in different ways

Dear Cross Validated Community, In a current project I have 4 different variables which can each be detrended in 3 different ways (which lead to non-negligible differences). Does it make conceptual ...
2 votes
1 answer
47 views

Mean of geometric distribution is odds?

Context: I mean the $P(X=k)=(1-p)^k p$ not the $P(Y=k)=(1-p)^{k-1} p$. Apparently the mean of the 1st kind of geometric is $\frac{1-p}{p}$ instead of $\frac{1}{p}$ for the 2nd kind of geometric. I ...
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0 votes
0 answers
4 views

Adjustment of multiple test in contrasts of contrasts

I have a model where I care about testing the differences among interaction terms. To make is more straightforward, I just use lm The model is : ...
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