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8 views

Correlating two normal variables only via their variances in R [closed]

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

Plotting accuracies obtained through three different methods

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 ...
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0answers
10 views

Is a Google Sheets fit model a valid place to retrieve starting parameters for nls() in R Studio?

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 ...
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0answers
10 views

Permuting outcome variable to estimate null likelihood ratio distribution for Poisson GLM

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 ($\lambda = e^{\beta_{0}}$)...
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0answers
6 views

Hurdle models in R: sign of the hurdle component coefficients

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 ...
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0answers
5 views

How to include two interactions which share one of the variables (`A`) in a linear regression? [closed]

Let's say I have a response variable Y, and I want to predict it using variables A,B and <...
2
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1answer
16 views

What is the defintion of variation in a box plot?

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 ...
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0answers
6 views

What would be best, using turnout levels or rates as the dependent variables?

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. ...
0
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1answer
14 views

Use bootstrap mean to remove bias from the statistic?

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 ...
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0answers
14 views

Existence of a random vector such that the differences of its components satisfy some restrictions

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}^...
2
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0answers
18 views

How is conditional expectation related to projection?

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 ...
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0answers
21 views

MLE for $\theta$ of unknown distribution [closed]

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 \...
1
vote
1answer
23 views

Probability problem - Probability to pick a subset divisible by 3

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 ...
1
vote
1answer
22 views

Ideas and good practices for reporting crude survival trends?

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 ...
0
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1answer
18 views

Training with oversampling

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 ...
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0answers
9 views

Asking the mean of food group that consisted of several food?

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 ...
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0answers
3 views

Tensorflow Hidden Markov model

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/...
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0answers
6 views

Alternatives to, or fix for, LMERConvenienceFunctions, for use with LME4?

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 ...
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0answers
6 views

Fraction below threshold across a population with individual variation, i.e. thinking about food

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 ...
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0answers
6 views

Stratified two-sample t-test in R

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. ...
0
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0answers
3 views

Model selection for panel data

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 ...
1
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0answers
7 views

How Gradient Descent is used for classification with Decision Trees?

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 ...
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0answers
19 views

Probability of selecting $U_{2}$ is?

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, ...
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0answers
10 views

Is my understanding and presentation of concept of Gradient Boosting correct?

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_{...
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0answers
22 views

Using Cauchy Schwarz inequality to bound the covariance [closed]

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.
1
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0answers
13 views

How can I simulate data for a linear model with random slopes and random intercepts [closed]

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 ...
0
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0answers
6 views

How to use tensorflow's module HiddenMarkovModel in pos tagging?

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 ...
0
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0answers
5 views

What should do when a smooth effect looks linear In a GAM?

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 ...
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0answers
7 views

Would a 3D CNN require less training samples than a corresponding 2D CNN?

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 ...
0
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2answers
32 views

Why are Poisson distribution and Exponential distribution special case of Gamma distribution?

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 ...
0
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0answers
12 views

How can I set the sample space for two random variables with 2 different discrete values for each? [duplicate]

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 ...
0
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1answer
17 views

Multivariate Jensen-Shannon divergence

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 ...
0
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0answers
4 views

Which Regression scoring to use when have small dataset?

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 ...
0
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1answer
33 views

To compare two KL-divergence scores, does the prior model have to be the same for both?

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 ...
0
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0answers
6 views

Can the label powerset method be used to predict probability for reach class?

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 ...
0
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0answers
10 views

Can $f$-divergences narrow the discrepancy between train and test fits in machine learning?

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 ...
0
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0answers
19 views

Prediction intervals from Linear regression and Arima

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 ...
1
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0answers
10 views

How Would I Perform the ADF Unit Root Test Manually?

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 ...
2
votes
1answer
12 views

Appropriate practice for setting seeds in permutation analyses?

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-...
0
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0answers
8 views

Analyze Fantasy Premier League using SAS [closed]

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 ...
0
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0answers
11 views

Expressing a joint pmf using CDF [duplicate]

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,...
0
votes
1answer
21 views

P value adjustment for pairwise comparisons of negative binomial

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 ...
0
votes
1answer
21 views

How to interpret random effect coefficients in glmer

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....
0
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1answer
16 views

Is this an instance of convergent evidence?

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 ...
0
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0answers
14 views

Some questions about linear model and generalized linear model (Are the process of building a model the same in these two models?)

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 ...
1
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1answer
26 views

Forward and backward stepwise regression (AIC) for negative binomial regression (with real data)

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: ...
0
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0answers
8 views

Different outcomes between XGBoost and GBM observation weights

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 ...
0
votes
0answers
11 views

How to find out if a set of time series regress towards the mean?

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 &...
0
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0answers
10 views

Best strategy to run thousands of small tests on a machine with one GPU and multi-core CPU [closed]

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 ...
0
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0answers
9 views

Confidence ellipsoides for unbalanced data with linear mixed model

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 ...

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