All Questions

Keeping the mean of x and y as 0, I was wondering if ...

I want to plot accuracies for 100 products obtained through three different methods. The data resembles the table below. What is the best way to represent visually these data? I was thinking of having ...

0 I am trying to fit an exponential model of form y = ae^(xb) in R to the data I have ran below, using the nls() function. I have read here and in other places that I need to feed the model reasonable ...

I fit a Poisson GLM using a set of candidate explanatory variables ($\lambda = e^{\beta_{0} + \beta_{1}x_{1}+\beta_{2}x_{2}+...}$), tested against the global null hypothesis ($\lambda = e^{\beta_{0}}$)...

I used to fit hurdle models with pscl::hurdle, I now use glmmTMB. The coefficients of the zero component of pscl::hurdle have the opposite sign of the coefficients of the zero-inflation component of ...

Let's say I have a response variable Y, and I want to predict it using variables A,B and <...

Variation is a term I have always been confused with. The first time I heard it, it was defined as "the different between the max and min values in a distribution". Lately, I've been hearing ...

I'm looking at the effect of a specific registration requirement on turnout and have been trying to decide what form the dependent variable should take. My two main options are turnout levels (i.e. ...

I have a data sample on which I apply a statistic called "$\alpha$". I then use a standard bootstrap analysis on the data which results in something like this: As can be seen, the bootstrap ...

Let us fix any three numbers in $[0,1]$ and summing up to $1$. I denote them by $p_1, p_2, p_3$. Could you help to show that, for every possible vector of reals $U\equiv (U_0, U_1, U_2)\in \mathbb{R}^...

I vaguely remember seeing somewhere that the conditional expectation $E(Y|X)$ can be interpreted as projection of random variable $Y$ onto random variable $X$. My question is: Is the aforementioned ...

I try to find the MLE of $\theta$ for this distribution above and i stuck \begin{align*} p_\theta(x) &= \frac{x+1}{\theta(\theta+1)}\exp\left(-\frac{x}{\theta} \right), \quad x>0 \quad \...

I'm trying to solve this puzzle but I get stucked. I thought about trying to use the law of total probability to solve intermediate problems with subset of size k but it didn't helped me that much. Is ...

I have 9-year-spanning data on patients survival (n = 10000). Each patient has a date of inclusion (got a diagnosis), which was used to determine the year of inclusion. Thus, temporal trends can be ...

I'm building a Random Forest model over an unbalaced 4 class dataset. So far I understood how to use oversampling and train my model. My doubt was about when to perform Oversampling. I've already seen ...

Hello i know this is a very basic thing but i just so confused. So i have several foods in a food group, for instance, for fritters group, i have fried tofu and sausage. I have the frequency (how ...

A decoding HMM has 3 parameters. But I am bit confused in tensorflow's HMM parameters and I'm not clear with docs https://www.tensorflow.org/probability/api_docs/python/tfp/distributions/...

Recently I updated from R version 3.6 to version 4.0 for my analyses, and noticed that LMERConvenienceFunctions stopped working. Specifically, I use it in conjunction with LME4. Whenever I try to use ...

For an individual, a parameter is known to follow a lognormal distribution:  $log(x_i) \sim Normal(\mu_i, \sigma_i)$ For a population, $\mu$ and $\sigma$ are known to follow a bivariate lognormal ...

Recently, I have started a project that needs to use stratified two-sample t-test. I know about one sample, independent two sample and paired t-test in R. My guess is that the project asks for ANOVA. ...

I was wondering about methods that could be used to compare different model specifications when dealing with panel data. In the case of cross-sectional data, a few applicable methods would be (in my ...

I'm not able to see how do we use gradient descent to minimize the loss of binary classification with decision tree. What I understood is that we first have a model (decision tree) that try to predict ...

A finite population has $N(≥ 10)$ units marked ${U_{1}, . . . , U_{N}}$. The following sampling scheme was used to obtain a sample $s$. One unit is selected at random: if this is the $i^{th}$ unit, ...

Initially the model is trained with a training set $\{x_{i}, y_{i}\}_{i=1}^{n}$ by minimizing a differentiable loss function $L(y, F(x))$, and, is initialized with a constant value, \begin{align*} F_{...

Using the Cauchy-Schwarz inequality, prove the following result The covariance between two variables cannot exceed 1/4 th of the product of the ranges of the two variables.

I have searched this site for existing answers but so far I didn't find anything. I did see this one How to simulate a random slope model Unfortunately it doesn't answer my question. I would like to ...

I want to do part-of-speech tagging using HMM. I want to use tensorflow module for viterbi algorithm. I know HMM takes 3 parameters Initial distribution, transition and emission matrix. But don't know ...

Recall the example in Wood, 2017 (Page.344), where a logistic GAM is fitted to a data set with some covariates all as smooth terms and then the estimated effects are plotted. Here is the effect of ...

I'm working with a problem where I only have several hundred training samples. That already sounds absurdly low, but I'm thinking: The relevant details for the problem are local patches within the 3d ...

I am aware that Gamma distribution is used as a conjugate prior distribution for various types of rate parameters such as in Poisson distribution and Exponential distribution. People say that ...

Say I have a group of athletes and I want to set two different random variables, $ X $ and $ Y $ to build a joint probability distribution of the two random variables. $ X $ has two different discrete ...

This paper says multivariate Jensen-Shannon divergence is $$JS(\mathbf{p}_1,\dots,\mathbf{p}_K) = \frac{1}{m} \sum KL(\mathbf{p}_i || \bar{\mathbf{p}})$$ with $KL$ being the KL-divergence of the ...

I am currently working on a Elastic-net regression assignment. The problem is I only have 40 training examples and I have to use 4 fold Gridsearchcv for hyper-parameter tuning. I am using sklearn for ...

The KL-divergence compares a theoretical model $p$'s distribution with the empirical model $q$'s distribution, giving a score of $0$ if they, or their information contents, are identical. Say we have ...

The label powerset is a method used to transform a multi-label problem to multi-class problem. The idea is straightfoward, just enumerate all the possible combinations of outputs, and treat each of ...

Machine learning models whose task is to predict unseen test data would work best if the test data's distribution turns out to be the same as the training data's distribution. Real data seldom works ...

I am comparing prediction intervals from linear regression and ARIMA for a simple AR(1) model: p = lag(p) The models were built on data from 2003-2013 years. Predictions were made for 2014 year. As ...

I am trying to gain a better understanding of the procedure of the ADF unit root test as I believe I am misunderstanding it. I have written python code that follows the steps below and I receive a ...

I am currently using permutation ANCOVA for a study of mine, in R, using the permuco package. Running multiple models for different brain regions of interest (ROIs). What I am finding is that the p-...

Is there any recommendations to analyze Fantasy Premier League using SAS? (or any other Fantasy League - mostly just looking for an interesting way to practice SAS) I see lots of resources available ...

A trivial question, but for some reason my mind is foggy and I could use some verification. We know that the joint bivariate pmf $P[X=i,Y=j]$ can be expressed using CDFs as follows \begin{align} P[X=i,...

Question 1) Am I appropriately doing the pairwise comparisons? Question 2) Why is the Sidak method used for the emmeans? Should I instead use adjust = "none" for these? Context: I have a ...

I am studing relationship between the competition facing a hospital and the death at 30 days within it. I performed mixed-effect model assuming that patient in same hospital should be more correlated....

In psychometrics, convergent validity is a source of proof for construct validity. It is said that it is the degree to which test scores are correlated with test scores of relevant constructs or the ...

I am learning linear regression model from the textbook "A Second Course in Statistics: Regression Analysis （seventh edition)" by William Mendenhall and Terry Sincich. There is a figure ...

I am doing some count data analysis. The data is in this link. Column A is the count data, and other columns are the independent variables. At first I used Poisson regression to analyze it: ...

I've noticed that the weights argument in the xgboost and gbm r packages don't have the same effect. I had hoped to move from gbm to xgboost for performance reasons, but am not sure how to do so given ...

I have a dataset with 10 year daily measurements (price earnings) of N similar stocks. I'm trying to figure out: if the daily median is stationary (otherwise it wouldn't make sense to talk about a &...

I have recently got a new machine with GPU and multi-core CPU. I have thousands of small tests (one minute each) to run in order to tune my model and extract some other information. What is the best ...

I am working with unbalanced data that contains repeated measures. I first run a mixed model after I have obtained my estimates I focus on a effect decomposition, from there I do a PCA. In the ...