All Questions
211,779
questions
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2
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Multiple IVs and DVs with non-normally distributed data
I am performing a research study aiming at answering the research question:
How does job design satisfaction differ between employees working in hybrid and remote work arrangements?
For that I ...
0
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0
answers
10
views
Showing that the estimator of the log posterior used in stochastic gradient MCMC is unbiased
In the SGLD paper as well as in this paper it is claimed (paraphrasing) that
the following estimator:
$$\widetilde{U}(\theta) = -\dfrac{|\mathcal{S}|}{|\widetilde{\mathcal{S}}|} \sum_{{x}\in \...
0
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0
answers
10
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Calculation of the Generalized Dice Loss Gradient
I am trying to understand the gradient of the Generalized Dice Loss (GDL) shown here Link. It says that the GDL for two classes is:
$$
GDL = 1 - 2 \frac{\sum_{l=1}^2w_l \sum_{n=1}^{N} r_{ln}p_{ln}}{\...
0
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0
answers
5
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Is there a known way of producing forecasts with reasonable fit and residuals that are at least independent, & ideally negatively correlated?
I am trying to do some forecasts. I have produced multiple forecasts by a variety of methods. All of the forecasts I have generated so far have residuals that are strongly positively correlated.I ...
0
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0
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4
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My results for chi square analysis is not tally with the visualized gbarstats
I am working on chi-square test to test for an associations between variables. I used
data_chi_GROUP = table(data$SEROPREVALENCE, data$GROUP)
...
0
votes
0
answers
20
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Purpose of expressing data in principal components
I have a rough understanding of the outline PCA. Given $n$ samples of $m$-dimensional data: $\vec{x}_1, \vec{x}_2, \dots, \vec{x}_n$, PCA aims to find an appropriate orthonormal basis called principal ...
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0
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7
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Infrastructure Score for Data Envelopment Analysis
I am planning to use survey questionnaire to determine infrastructure score with relevance to its quality and quantity. Can I use this for a DEA study? and to what extent?
0
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0
answers
3
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Including Covariate P-Values in Multiple Comparison Corrections"
I'm currently working on a statistical analysis involving multiple comparisons and I'm uncertain about a specific aspect of the process. Specifically, my question is about the inclusion of p-values ...
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0
answers
14
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How do we prove that the rows or columns of a hat matrix sum up to 1, when mean function includes an intercept?
Every textbook I encounter tells me that this is simply a meaningful relationship of a hat matrix, without explaining why:
If H is the hat (projection) matrix, and our X matrix has full rank and a ...
0
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0
answers
7
views
Converting a stata program to SAS
What is the equivalent of the following stata program to SAS?
regress weight height if age==1
est store age1
regress weight height if age==2
est store age2
regress weight height if age==3
est store ...
0
votes
0
answers
6
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Diffrence in logs vs. a % changes in econometrics: why is the dif log approvimation almost always used when the exact quantity is easily available?
I have observed that in econometrics work people almost always use the difference in logs rather than the actual percentage change. This makes no sense to me. I understand that the difference in logs ...
2
votes
2
answers
32
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Computing Z scores AP Psych
My report is looking at the effect of belief in conspiracy theories and critical thinking abilities, on engagement in politics.
I've basically got to do a factorial ANOVA and my IV's are:
Conspiracy ...
1
vote
1
answer
11
views
Impute missing value [closed]
In machine learning when I impute missing values which of the following I perform :
1-Impute data set and then split it?
2-Split dataset to Training and testing datasets and then Impute each datasets ...
1
vote
0
answers
18
views
Motivatation behind moving average models [duplicate]
Suppose I have a time series with mean $0$. If I was assuming an $MA(1)$ model, then my prediction at each time $t$ would be proportional to how "off" my last prediction was.
This feels ...
0
votes
0
answers
5
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Time order problem of control variables in IV regression
Y is the dependent variable, X is the independent variable, and C is a control variable. However, since X is endogenous, I plan to use an instrumental variable Z for X. From what I understand, if I ...
0
votes
0
answers
5
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Beyond AR(1) as a covariance structure for mixed models with repeated measures
I have been reading about alternatives to assuming an AR(1) covariance structure for mixed models with repeated measures (in time). In particular I have heard about Toeplitz and Ante-dependence ...
0
votes
0
answers
10
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Why is validation accuracy fluctuating between two extremes?
I am using a LSTM to make a multi-label classifier. However the problem is, the validation accuracy fluctuates between 0.7 and 0.3. I have about 4367 samples (80-20 validation split) and 240 sample ...
0
votes
0
answers
7
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Rationale for box-constrained optimization in adversarial example search
In Section 4.1 of "Intriguing properties of neural networks" by Szegedy et al., the authors define the optimization problem they solve to find adversarial examples in a deep neural network. ...
2
votes
0
answers
22
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Does applying a variable transformation to experiment data result in p-hacking?
From formal statistics classwork and some research experience, I understand that it is widely considered standard practice to apply transformations to predictor variables for conducting significance ...
1
vote
0
answers
13
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Best Textbook for a Rigorous Treatment of Panel Data
I was wondering which book you recommend for a treatment of panel data that is both rigorous and intuitive. What do you recommend among Wooldridge(2010), Baltagi(2021), and Hsiao(2022)? I studied ...
1
vote
0
answers
27
views
Expectation of the Gaussian likelihood
I'm working on a challenging machine learning problem, where I need to find the expectation of the likelihood of one Gaussian, given the parameters of another. Apologies if any of the notation is ...
0
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0
answers
21
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Calculate multivariate betas using correlations and standard deviations [duplicate]
In a simple regression context:
$$
y = \alpha + \beta x + e
$$
We can estimate beta from:
$$
\hat{\beta} = \frac{cov(x,y)}{var(x)} = \rho_{xy} \frac{\sigma_y}{\sigma_x}
$$
This last decomposition is ...
0
votes
0
answers
27
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How to classify lists of 2 values (a,b) according to how close values of b are to another value of b?
I'm hope this is the correct forum for this but the gist of the problem is this:
If I have a list of 12 values like this: 0,0,0,1,0,0,0,1,0,0,0,1 - then my frequency rate of 1 is 3/12 = 25%
The same ...
1
vote
1
answer
65
views
What is the posterior probability for flipping a coin, assuming a beta distribution as conjugate prior
Suppose, I toss a fair coin n = 10 times and get 7 heads and 3 tails. The probability of fair coin is p = 0.5. Now, that the beta distribution is a conjugate prior of the binomial likelihood. I used ...
0
votes
0
answers
14
views
Question about Gaussian Mixture model [duplicate]
suppose I have two parameters:
$(\mu_{1},\Sigma_{1},\alpha_{1},\mu_{2},\Sigma_{2})$ and $(\mu_{1},\Sigma_{1},\alpha_{1},\mu_{2},\Sigma_{2})$ and suppose I mapped them to PDF using the gaussian mixture ...
0
votes
0
answers
9
views
The least-squares dummy variables estimator vs fixed effects estimator in panel data
Is the least-squares dummy variables estimator never more efficient than the fixed effects estimator?
I mean both should be consistent under the same assumptions. Quite often we assume in panel data a ...
0
votes
1
answer
29
views
do marginal density functions derived from a joint pdf always integrate to 1 (are they valid pdf's)?
If I have a joint pdf of multiple random variables, say 3 for simplicity, $f_{X,Y,Z}(x,y,z)$, is it true that the marginal density functions derived from that joint probability distribution ( $f_{X}(x)...
0
votes
0
answers
9
views
Evaluating and comparing forecasting methods through errors in multi dimensional time series data
I have a fairly complicated problem and I would like some advice on how to properly assess the results.
I have a series of 12 connected 'zones' that have a specific numerical value at any given point ...
0
votes
0
answers
22
views
How to graphically represent a Probit regression after weighting using propensity scores in R?
So I have a Probit model that uses weights w, which I got from propensity scores, but I can't find any information on how to represent the Weighted Probit regression. All the information I could find ...
1
vote
0
answers
14
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Reporting fixed effect estimate and error bars for log transformed output variable in mixed effect model
I have a linear mixed effect model I am fitting using lmer:
...
0
votes
1
answer
17
views
Statistical or Machine Learning Approach for Simulating Variable (proportion)
I am currently facing a challenge in analyzing customer satisfaction data from an electric drive production facility. During a specific period of the month, we encountered technical issues with our ...
0
votes
0
answers
10
views
Mutation probability for simple and complex problems
Is It always better increase the mutation probability if the problem is more complex?
I'm doing different experiments trying to check if a higher mutation probability helps to find a solution when the ...
0
votes
0
answers
14
views
Quantile regression in SAS vs Python [closed]
Given this dataset
...
0
votes
0
answers
13
views
A question of "elementary imsets" in an ADMG
In [The m-connecting imset and factorization for ADMG models] (https://doi.org/10.48550/arXiv.2207.08963), it was mentioned the notation of an "elementary imset". The definition of ...
0
votes
2
answers
64
views
Prove that OLS estimated coefficients are independent from other variables
How to prove that OLS estimators do not depend on other parameters, given the same variables are included in the regression?
I generate some random data for 30 observations and 4 variables $x_1,x_2, ...
1
vote
0
answers
9
views
High Standard deviation for regression coefficient in multilevel model with random slopes compared to fixed slopes
Recently, I compared two multilevel models of the same data:
One with fixed slopes:
R Code: lmer(RT ~ Kontrast + (1|ID) + (1|Satz),
data = reading_times,
REML = F)
and one with random slopes:
lmer(RT ~...
0
votes
0
answers
14
views
For relationship between cycling and weather variables: multivariate linear regression? PCA?
Ive been having some trouble determining which analysis to run for a project of mine looking at the relationship between cycling and env variables. I would like to include two different types of ...
0
votes
0
answers
14
views
Making a multiclass classification problem binary during data preprocessing vs using a multiclass classifier
Sometimes you have a problem that presents as a multiclass problem in your data, but you only care about the result of a binary classification. E.g. you have a manufacturing process which can result ...
1
vote
1
answer
144
views
Are there cases where we need to avoid the usage of IQR?
Let's consider the interquartile range (IQR), the standard deviation (SD) and the mean absolute deviation (MAD). We know that "one of the most common robust measures of scale is the interquartile ...
0
votes
0
answers
15
views
Retrieving the variance partition coefficient of the frailty() term (mixed effects) for cox regression in R
I am new to running survival analyses. I am attempting to construct a cox regression using the coxph() function. I want to include a ...
1
vote
0
answers
25
views
Should I delete samples from the training data that are present in the testing data by accident?
I classify pairs of entities, let's say dog-cat pairs, whether there is association between them (positive class) or there is not (negative class). I have a moderately sized positive dataset (~130k ...
0
votes
0
answers
15
views
Test for whether method decreases the metric or not
we have created a software for a given task. What we wanted to achieve is 1) to speed up the process 2) without lowering the quality of the work. Now I would like to run a test to see if 2) stands. My ...
0
votes
0
answers
20
views
Paired Comparison on $n$ Tests, Repeated $k$ Times Each
Suppose I test two subjects on $n$ pass/fail (Bernoulli) tasks, $k$ times each—for a total of $n\cdot k$ tests per subject. I want to compare the subjects to see if there is a statistically ...
0
votes
1
answer
31
views
Expected values conditioning two different expressions of a discrete variable
Suppose that we have two continuous random variables $Y$ and $X$ and a discrete random variable $W$.
The discrete variable $W$ can have only three values 1, 2, or 3. That is, $Supp(W)=\left\{1,2,3\...
0
votes
1
answer
50
views
what is the difference between these two expressions
What is the difference between
$$ \frac{exp^{-\beta_j}}{1+exp^{-\beta_j}}$$
and
$$ \frac{exp^{\beta_j}}{1+exp^{\beta_j}}$$
From an application perspective ?
0
votes
0
answers
12
views
Based on the below data, the y-variable increases by 50% as x increases by 1, but the log transformed shows a different % change. Why so? [closed]
x: 1,2,3
y: 10,000, 15,000, 22,500
After taking the logarithm of the y-values, my calculations indicate that the y-value increases by 17% as x increases by 1.
Where did I go wrong?
0
votes
0
answers
34
views
Is there a heavy traffic approximation of percent under benchmark?
Suppose I have an waitlist of patients waiting to be served. Each patient has a benchmark number of days that the service should be completed by as a goal (not a hard constraint of the modelling). ...
0
votes
0
answers
40
views
Time Series Estimation
Assuming $\{a_t\}\overset{{iid}}{\sim} N(0, 1)$, and the model is both causal and (weakly) stationary.
As we have $E(Y_{t-1}a_t) = 0$ (causality), $E(Y_t) = 0.5\mu$, right?
But I am not sure on the ...
0
votes
1
answer
27
views
Is there a way to enforce factor importance in random forest/xgboost
Suppose I have 3 predictors to predict stock returns. 1 of the 3 is known for ages and is still doing well. The rest 2 are newly found ones. So in a crude portfolio construction fashion, I'd do $s = 0....
2
votes
0
answers
41
views
null model in glmnet
With lm models I can construct a null model like this:
lm(y ~ 1, data=df)
What would the equivalent be in ...