All Questions

I'm trying to ascertain whether the variance explained by a certain PCA on an out-of-sample dataset is not due to random chance. Suppose I have a dataset X with size n-x-p, and I run a PCA and obtain ...

There's this dataset containing the metadata of Twitch's top 1,000 streamers of 2020. You can have the details here. I am currently participating in a challenge to predict the values for Followers ...

I am working out with the thesis paper Cheang(2018) to calculate synchronised returns between two stocks from different markets. I am trying to code this in R. I am using rmgarch package and using <...

Below you can see the code for convolution of two continuous functions. There is a function called fx which I took as the square root of a Gaussian distribution. The convolution is calculated using 2 ...

From my little knowledge of statistics, a sample is a subset of a population. Now I am reading a textbook on mathematical statistics. In the introductory section of the chapter on sampling ...

Basically i am investigating the impact of monetary policy on agriculture per worker using semi-annual data by employing vecm.

I am interested in looking at something like this: https://cran.r-project.org/web/packages/heemod/vignettes/c_homogeneous.html Suppose there is an insurance company. The inaurance company processes ...

Suppose you have dataset with 10 variables (e.g. var1, var2, var3, etc.) . If you wanted, you could calculate the correlation between each pair of these variables (i.e. 10 C 2 = 45). But does such an ...

This probably has a very simple answer and I'm just overthinking it. I have a very large dataset (~30,000 individuals), that contains data on casualties seen at a wildlife rehabilitation hospital. I'm ...

so Ive been studying multiple imputation and I dont quite get it. Suppose I have two variables Y and X with Y has some missing values and the missing mechanism is MAR. Suppose I use stochastic ...

Let's say I have the typical ANOVA where X has 3 categories and I one hot encode. I then have: Y = b1X1 + b2X2 + b3X3 b1, b2, and b3, are basically how much mean(Y | X) deviates from 0 (and if the ...

I know that in general for random variables $X$ and a function $g$ $E[g(X)]\ne g[E(X)]$. I would like to know when the following holds $E\Big[\frac{cov(X,Y|Z)}{var(X|Z)}\Big] = \frac{E[cov(X,Y|Z)]}{E[...

NLOGIT software allow to edit the utility function for each alternative. Format looks like below, ;model U(alternative 1)=<utility function 1>=constant1+coefficientsvariables U(alternative 2)=&...

Hi I have a base with p=40 and n=11750, I want to build a model with Ridge classifier (because the objective is predictive if one person is going to be defaulter=0 o not defaulter=1) that select the ...

Suppose that $X$ and $T$ are both random variables. Where $T$ is a label. I just want to ask is tha finding probabilities on the label $P(T=t)$ or conditional probabilities $P(X=x|T=t)$ meaningful or ...

Here is my setup: I have M=200 municipalities who all rank high in corruption For each municipality, I pick a random sample of ...

I am working on an exercise using conversion rate data on a travel website. The conversion rate is defined as the number of users in a given time period that make a purchase. There are two groups, A ...

I have a point of confusion regarding the three types functions. I have looked at some other posts here and blogs and scripts and YouTube videos. But I still don't get it. Let's look at the coin toss ...

I wanted to create a supervised NN that recognises numbers on images from scratch, pretty ambitious project for someone like me. But when I test it with a simple XOr gate, it completely fails. It just ...

Suppose we have two healthy but curiously mixed boxes of fruit, with one box containing 8 apples and 4 grapefruit and the other containing 15 apples and 3 grapefruit. One of the boxes is selected at ...

Given a set S of unique marbles (with s = |S|) and bags with m marbles in each bag, what is the expected number of bags that would need to be collected to have a subset containing at least 1 of each ...

I'm attempting to model how 2 predictor variables affect the relative proportions of 3 different categorical groups. I started off by running a binomial model for the proportion of each individual ...

In non-time series, regression models when we say "heteroskedasticity" we almost always refer to "conditional heteroskedasticity". For example, the Breusch-Pagan test is a test for ...

I am trying to optimize an SVR model within the mlr3 ecosystem with the kernlab package and I am getting the following error: The parameter 'C' can only be set if the following condition is met 'type &...

Background: I am running a model selection in R that includes 1, 2, and 3-covariate models. Each model aims to determine the effect of environmental covariates in the occupancy of different species in ...

My binary dependent variable (pollinator presence) responds to the independent variable (air temperature). With increasing temperatures there is a logistic increase in probability of pollinator ...

I wonder if the Mixed Logit model could be understood, stated, and estimated as a Generalized Linear Mixed Model. Mixed Logit Consider a standard discrete choice setting where individual $n \in \{1,......

I have a fairly basic mathematical and implementational understanding of ML algorithms and CNNs, and I am trying to think of an approach for this task: https://www.kaggle.com/c/rsna-miccai-brain-tumor-...

I have trained a regression model with 7 features for a given problem. Now, I have another regression problem (quite similar to the previous one) where I have only 6 samples in hand, but with 3 more ...

I have an AxBxC matrix of measurements, from which an arbitrarily-sized-and-distributed number of measurements have been deemed invalid and removed (i.e. that matrix contains a mostly random ...

We performed a 45s test with dogs and humans, we measured the distance between the dog and the human every 0.25seconds with GPS. The data for one subjects are in the following format: Subject_Id ...

To briefly explain what I've been working on, I have two datasets: one as a reference(larger) and another for validation. I performed the PCA analysis with my reference dataset to create the ...

I am very new to R and statistics in general, so it is likely I am adopting the wrong approach. I have a large dataframe made of binary, character and numeric variables with n observations per year. ...

I am reconciling two time series, $X_{1...n}$ and $Y_{1...n}$. They are supposed to have close to 100% correlation, but in reality often not. When that happens, I want to quickly find the points that ...

I'm new to Neural Networks, and in whole to Machine Learning, so excuse my lack of knowledge on this subject and please bear with me. I am trying to train a shallow network (2 hidden layers, 15 nodes ...

I am trying to simulate data for a longitudinal multilevel model. Let's say I want to simulate 4 observations of random variable X for N persons - how would I do that assuming autocorrelation of X to ...

The naive Bayes classifier assumes the regressors to be mutually independent, while linear discriminant analysis (LDA) allows them to be correlated. James et al. "An Introduction to Statistical ...

What can I do to make Student-T priors in a brm Bayes model less tall? Particularly this is a linear model: $a+bx$ And my current priors are: ...

I have a data set with aggregated data of two study groups. Twenty response variables were recorded for each group and for each response variable, the group size, mean, median, and the 5 and 95 ...

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I have two paired vectors which report the number of times each object was found in the two experiments (the count value could be 0 or greater (e.g. 5,10,1000, etc)). I want to compare them and get a ...

With reference to this post on feature scaling, and many tutorials out there, it is mentioned how we should avoid data snooping by performing say, feature scaling on the train set, and then use the ...

I am doing regression kriging for a certain pollutant as a dependent variable, and for independent variables I'm using 4 variables that add to 100% for all observations. Because of this when I use ...

I am using the pcor.shrink function from the corpcor R package to compute the shrinkage estimates of partial correlation ...

When you formulate a fixed effects panel regression model for observed data using the within estimator in R package plm, can there still be endogeneity present if there is error in the explanatory ...

2 possibilities : A1 . B1 . C1 A1 . B1 . C2 so how we calc each one percentage ?,

I will like to obtain the p-value of a lakagami distribution. Let say I have the following: ...

Let $Z_n =Z+W_n$ where $Z \sim N(0,1)$ and $W_n$ is a binary random variable taking $n^2$ with probability $1/n$ and $0$ otherwise. Then for $M<\infty$, $E(|Z_n| 1 \{|Z_n|>M \}) \ge E(|Z +W_n|...

I'm doing a retrospective study where I want to analyze whether a certain treatment (surgery A vs. surgery B) has an effect on the health status after the surgery measured with different parameters (...

I want to extract gene expression data for each cell and I wonder which option in “slot” to use to get log normalised data? is it “data”, “scale.data”, or “counts”?. I’m confused and I really want to ...