All Questions

0
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0answers
11 views

multcomp() vs emmeans() for multiple comparisons

I have two sets of models. The first set contains a number of logistic models, fitted using glm(), with different binary dependent variables. The second set ...
-1
votes
1answer
7 views

How to compare different clusterings of the same data

If I have two groups of clusters of the same data (e.g. that were created using different modalities), what's a standard/established way of discovering interdependencies/relationships between the two ...
0
votes
1answer
8 views

Dataset documentation and schemas

When working with databases one typically specifies a schema, describing the data at least on a very coarse level. Often, one does not use a database, but loads the data in memory, into e.g. a pandas ...
0
votes
1answer
18 views

How to allocate unclassified observations proportionally within classified data?

In my dataset, about 30 percent of all observations belong to a unclassified category. Since I want to account for the effect of these observations, I want to allocate these unclassified observations ...
0
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0answers
6 views

how the natural policy gradient simplifies?

in David Silver RL course page 37 for "natural policy gradient" Using compatible function approximation we have: So the natural policy gradient simplifies: my question is how the above equation ...
3
votes
0answers
31 views

Looking to identify a book by a top statistician with a chapter on Simpson's Paradox

It was more than 20 years ago. I had just gotten acquainted with Simpson's paradox. I was browsing in a bookstore and saw a book by an eminent statistician -- eminent in the sense that I had come ...
0
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0answers
12 views

Coding Random Forrest in R

I'm looking to code a random forest in R but am having a bit of trouble in my dataset. Before I get into the problem, let me reproduce my code below. The response variable of interest is '...
0
votes
1answer
22 views

How to find the “variance” when using “central limit theorem” on a Poisson distribution?

Assume we have N number of inventors. All inventors work at a company. Each inventor expects to invent X number of inventions per year. How many inventions they invent per year has a "Poisson ...
0
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0answers
3 views

How to interpret LDA (Latent Dirichlet Allocation)?

Say I want to run topic modeling with LDA on The 20 newsgroups text dataset. So basically a dataset with texts where every text belongs to one of 20 categories. I want the LDA to split the documents ...
1
vote
1answer
39 views

Gamma distribution parameters estimation

I have a set of samples taken from a population distributed with a Gamma distribution, so \begin{equation} f_X(x)=\frac{\beta}{\Gamma(\alpha)}x^{\alpha-1}e^{-\beta x} \end{equation} I should estimate $...
0
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0answers
13 views

Calculating predicted value from polynomial regression by hand

I have the following output from from R. I know we can calculate predicted values using the predict() function. How can we calculate the predicted value by hand if X=2 or 3? I'm using the below ...
0
votes
0answers
12 views

Measuring distance preservation in dimensionality reduction

I am looking to compare the distance preserved during dimension reductions for several techniques. I have read some papers on similar topics here and here. For example, I would like to use the ...
0
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0answers
12 views

Inference can be the goal of an unsupervised learning method or a semi-supervised learning method or even more of a reinforcement learning method?

I am new to machine learning, and I am reading a pair of machine learning books. These references talk about 2 different learning approaches: Prediction and inference, I understand the difference ...
0
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0answers
13 views

Should the predicted variance in Gaussian process regression include experimental error?

Suppose I have an experiment where I measure the temperature of water in a cup, $y$, as a function of time, $x$. My measurement is normally distributed with an experimental uncertainty given by $\...
0
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0answers
6 views

Correlations and Hierachical Regression

For my dissertation I've carried out a hierarchical regression. My results have shown: -correlations. Neuroticism is correlated non significantly .000 on SPSS to my dependent variable. Mood is non ...
0
votes
0answers
5 views

Fuzzy Regression Discontinuity and Instrumental Variables

What is the logic behind using an IV for a fuzzy RD?
0
votes
0answers
21 views

Find UMVUE of $p^3$

Let $X_1, X_2, ..., X_n$ be a random sample from $Binom(1, p)$. I'm trying to find the UMVUE of $p^3$. Some thoughts: Apparently, $\bar{X}^3$ is not the answer, although it's the MLE of $p^3$. For ...
1
vote
0answers
11 views

Aligning and clustering sequences of events

I have some data describing sequences of events. There are a number of different events (over 30), and the data records which event occurred in what order. There are no fixed number of events that ...
0
votes
1answer
10 views

I ran an ANN model and got an extremely low R2 but a pretty good MSE, what does this mean?

I ran an artificial neuron network on data with about 2,000 rows and 3 features. I got a R2 of .06 which is really low, but a good MSE of .41. Why are these performance evaluators of this model ...
0
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0answers
19 views

Understanding backprop equations

I was watching a video on backprop from deeplearning.ai where one particular thing confused me a lot. In the backprop, as shown below, Why aren't we averaging <...
0
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0answers
5 views

Bayes vs trial factor (particle physics)

In the statistical inference for particle physics is the trial factor analogous to Bayes factor but for the frequentist analysis?
2
votes
2answers
28 views

why did the subset and factor influenced coefficients of logistic regression in R

The coefficients changed a lot when I used all the factor levels versus when I limited to only one level of a factor as a subset of the data. I am trying to do a logistic regression between the ...
0
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0answers
4 views

Approximate Bayesian Computation: Applications to Elevator Group Control Systems

I am working on a project where I will be using Approximate Bayesian Computation (Likelihood-Free Inference) in order to improve an Elevator Group Control System, e.g. minimize the waiting time of the ...
0
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0answers
7 views

Difference between Granger causality and Instantaneous causality?

What is the difference in terms of inference? Does Instantaneous captures the short term cause and effects?
0
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0answers
12 views

Score test for multiple parameter model

Suppose I have a multivariate linear model: $y = Z\bar{\alpha} + x\beta + \epsilon$ Where $Z$ is a matrix of covariates and $\bar{\alpha}$ are their effects. I refer to them as covariates as I am ...
4
votes
4answers
215 views

Understanding p-Values using an example

I know there might already be tons of questions around understanding the interpretation of p-Values, however I would ask the question in a very limited form and with the use of a specific example ...
0
votes
0answers
5 views

Appropriate analysis for univariate proportion data and environmental variables

I'm new to statistics so am trying to choose the best analysis to find if; There is a difference between canopy cover (0-100%) at different sites There is a relationship between canopy cover and ...
0
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0answers
6 views

Control for two variables in repeated measure ANOVA

I have a 2 factors repeated measure ANOVA for measuring Response Time to stimuli in two different contexts with two different stimulus types. The context and is not supposed to have any main effect. ...
0
votes
0answers
23 views

How to interpret the Z Value in probit regression summary

I am running a Probit model in R and find trouble interpreting the Z Value of -9.974. Obviously, it is not the same as the Z-score. So how do I interpret it and is t the same as the t-statistic on my ...
0
votes
0answers
11 views

Friedman and Kruskal

I have a data with 4 groups and multiple variables with measured values. my groups are ES, EP, PP and PS. ES and EP are associated and PP and PS are too. So i would like to compare my groups in non ...
2
votes
1answer
36 views

On a mistake computing the Kullback Liebler Information Criterion

THE FRAMEWORK: Let $X_1$ be an observation from a normal random variable with mean zero and variance $\sigma^2$ and lets call the PDF $f(x)$. I want to minimize the Kullback Liebler Information ...
0
votes
0answers
8 views

Effect size for linear models

I´m running simple linear models in R y~x but always got a really small R², although the p-Value always shows significance!. Now I wanted to calculate an effect size because I want to know whether ...
0
votes
0answers
18 views

Comparing the First Names in two population samples

I'm not great at stats and hope for a bit of help ... I have two sets of peoples first and last names the first group has about 5000 unique first and last names and the second about 300. When I ...
1
vote
1answer
25 views

can you help me to do a difference of CDF?

I have 2 CDF's with equal number of points that I want to compare. These are from: Temperature of 1 month from 2012 Mean temperature across months What can I do to obtain this difference, this is ...
0
votes
0answers
10 views

Random effect VS Pooled OLS

I am a second year MSc ACFN student at Addis Ababa University, Ethiopia. Now, I am conducting my research on the "effect of leverage on profitability and I use a panel data". When I was trying to ...
0
votes
0answers
16 views

How do you define the error in a hidden layer of a neural network?

I am reading some introductory texts on neural networks. While I am able to understand that the error in the final layer of the neural network is but I am not able to understand how the errors in ...
0
votes
0answers
5 views

Why is the reward fluctuating for Double Q-Learning?

I am trying to implement Double Q-Learning using neural networks from the Keras library. When I first tried Simple DQN, the graph of the reward was fluctuating a lot so, I implemented a Double DQN. ...
0
votes
0answers
10 views

How do I put back the name of website together with the data scrapped? [on hold]

I have two columns "name" and "link" which indicates the name of the firm and the link to scrap from. How do I put back the name column so that each row of scrapped data will have a column with the ...
3
votes
3answers
43 views

Iterated expectations and variances examples

Suppose we generate a random variable $X$ in the following way. First we flip a fair coin. If the coin is heads, take $X$ to have a $Unif(0,1)$ distribution. If the coin is tails, take $X$ to have a $...
-3
votes
0answers
14 views

Abandoning statistical significance is both sensible and practical? [on hold]

1 Why statistical significance is not a good tool in experimental studies with human subjects? Wittingstein -Complicated experimental design -Mother tongue (explanation of the experiment by the ...
0
votes
0answers
20 views

cumulative distribution functions (CDFs) [on hold]

i want to know why is important use CDF for this analysis of TMY (typical meteorological year) because i have the data of the month for compare with the long term mean This the example of the manual ...
1
vote
1answer
12 views

Proving that Shannon entropy is maximised for the uniform distribution

I know that Shannon entropy is defined as $-\sum_{i=1}^kp_i\log(p_i)$. For the uniform distribution, $p_i=\frac{1}{k}$, so this becomes $-\sum_{i=1}^k\frac{1}{k}\log\left(\frac{1}{k}\right)$. Further ...
0
votes
0answers
12 views

Dirichlet Process Mixture Conditioning

Suppose I have a Dirichlet Process Mixture model defined as follows: $\alpha \sim G(a,b)\\ \pi|\alpha \sim \text{Dir}(\alpha)\\ z|\pi \sim \text{Cat}(\pi)\\ $ where $G$ is just a standard Gamma ...
0
votes
1answer
20 views

Feature engineering with cross validation, then testing on a holdout data set?

We have 3000 samples for two classes, roughly 2000:1000. Our plan is to train a classifier on the samples but first to set aside 30% randomly selected stratified samples as a "holdout data set" for a ...
0
votes
0answers
11 views

How to calculate bootstrap values for Fst?

I want to try to get the significance of my Nei Fst values through bootstrapping. I have a large data set of SNPs from RADseq data. They are in 4 populations: River, Lake, Outgroup1, Outgroup2. My ...
0
votes
0answers
13 views

What happens if pooling kernel size is equal or larger than input size?

I always know that kernel size should be smaller than input size. I wonder what if the opposite. For example, if I have a 2d average pooling layer: Input size=4X4, Kernel size=6,Stride=1,Padding = ...
2
votes
1answer
137 views

If one coin toss yields Head, what is the PDF for the probability of a head?

This is not a homework question. I discovered that I am not the only tenant in a highrise that is getting headaches from paint fumes. I talked to one couple in the elevator about the paint fumes. I ...
0
votes
1answer
17 views

Mathematical Motivation of Splitting Into Training and Testing Sets

In Learning from Data course taught by Caltech Professor Yaser Abu-Mostafa the following notation is used to describe the in sample and out of sample errors. $E_{in}[h]=\dfrac{1}{N}\sum_{n=1}^Ne(h(...
0
votes
0answers
7 views

Proof for multicollinearity consequence

I came across this statment "Even extreme multicollinearity (so long as it is not perfect) does not violate OLS assumptions. OLS estimates are still unbiased and BLUE (Best Linear Unbiased Estimators)"...
0
votes
0answers
11 views

How can I use repeated cross-validation to report out-of-sample prediction performance?

I'd like to better understand how to report the out-of-sample prediction performance using repeated k-folds cross-validation. I think I have a reasonably good understanding of the motivation for ...

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