All Questions

138,858 questions
4 views

What are the two main parameters in K-Means? [on hold]

What are the main parameters in K-Means and What is the main problem of K-Means clustering algorithm
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How do I prepare my data for sequence analysis in STATA? [on hold]

This is my first time performing sequence analysis, I want to come up with precarious employment trajectories, so I have already some variables prepared that measure in months when was a specific ...
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How to calculate contribution, ROI, and mROI from marketing mix model?

I've begun to read the books MARKET-SHARE ANALYSIS and Market Response Models on how to estimate marketing mix models, but, while they thoroughly detail how to model the response to promotional ...
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How to correlate values in the same column by group using groups in another column

I have a dataset that looks like this in R: ...
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IOU vs ROBIN metrics

Came across this paper on ROBIN evaluation metrics. The metrics seem to be more informative than just IOU, so is there a reason why IOU is the preferred metric in most cases for object detection. ...
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How does one compare two nested quasibinomial GLMs?

Lets say I have two models: Model 1 and Model 2, both of which are used to fit a quasibinomial GLM on some 0/1 response data (that I believe has overdispersion, hence quasibinomial GLM instead of ...
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Adapting Cox Regression to Time dependent continuous variables

I am interested in using cox survival regression model when the covariates are not expected to be constant over time and also continuous. I did check a few books and the time dependent Cox Regression ...
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Calculating the posterior distribution of linear predictor

I am currently fitting a linear regression model in a bayesian framework in R with the package ngspatial. To investigate the quality of fit, I would like to calculate the bayes R2, as suggested here ...
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How to check if i have strong linear relationship between dependent variable and independent variables in ols?

I want compare the out of sample prediction from an ols model and a regression tree. I read that ols outperforms regression tree if the relationship between the dependent variable and independent ...
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Is Oversampling beneficial in semi-supervised learning?

I have suggested a semi-supervised approach for the hierarchical multi-label classification task. I have included the MLSMOTE oversampling technique as a pre-processing step, and then evaluate the ...
9 views

Linear Programming/optimisation with R? [on hold]

I hope this isn't a repeated question, but: does anybody have a firm idea of how much data can be handled by R when doing a linear optimisation model? For example, will R be able to handle ...
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Understanding PCA from a linear transformation perspective

I've came across several great questions and answers here regarding PCA, but I would like to have a look at it from a linear transformation perspective. Let's say I have a (demeaned) data matrix $X$ ...
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Should subscales be analyzed separately under the IRT Graded Response model?

Suppose I have a Likert scale type questionnaire that assesses the amount of social support a patient receives. The questionnaire is divided into four subscales that measure: Emotional support ...
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Parametrs of the Uniform Likelihood

Consider linear scalar model $y_k = x_k + w_k$ where $w_k \sim U(a,b)$. What we can say about the probability distribution $p(y_k|x_k)$? We can show that $p(y_k|x_k)$ have uniform density, but I ...
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Error in R Random Forest package [on hold]

This is my train_set: I'm trying to predict monetary using RandomForest package with: <...
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Can I work around a small number of samples in a logistic regression? [duplicate]

I am deeply frustrated, I have a dataframe with a small number of samples (N=13) and am trying to do a logistic regression with binomial variables. I know, that especially given that there is an even ...
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K-Fold Cross Validation: Bias in cross-validated effect size measures?

As pointed out by various authors (e.g., Hattie, 2011), K-fold cross-validation has an upward bias of prediction error. I wonder whether the same holds for cross-validated effect size measures such as ...
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How to transform a non-stationary time series with short spikes to stationary?

I used ADF test to test stationarity: ...
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Predict Taking a Loan

I want to build a Logistic Regression model to help me predict taking a loan by a customer base on several variables. I started building a data set for the customers who already took loans and some ...
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how svm from e1071 works with k>2

I'm pretty new to R and machine learning and I'm doing an analysis on a dataset. I'm tryng to use the svm function from the e1071 library but I'm wondering if it takes care of number of classes. I ...
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Minimax equivalence of Matrix Norm

In a proof of random matrix theory, the author makes use of the following equivalence: $$\inf_{v\in V(r)}\lVert Xv \rVert_2 = \inf_{v\in V(r)} \sup_{u \in S^{n-1}}u^TXv$$ ...
21 views

Interaction significant, simple effects not

I'm running a regression which showed a significant interaction effect between my variable design (0,1) and device (0,1) on view time. However, i did not found a main effect of design on view time. ...
10 views

Multiple non-linear regression with weak correlation [on hold]

a question about multiple non-linear regression. What I did - using GAM family = Poisson regression, my goal is to estimate the relationships among variables. ...
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Glmnet default values [on hold]

I am using the glmnet package to find biomarkers from a dataset. I only tell the function my x and y vectors and my alpha but no family (such as binomial, gaussian etc.). What would be the default ...
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Doubt in Monte Carlo sampling [on hold]

I came across this in page 491 of the book "Deep Learning" by Goodfellow: I wanted to know what exactly are they doing here? I could not understand the statements being made to justify the sampling ...
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How to analyze correlation of multivariate time series

I have a multivariate time series with variables A, B and C. ...
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Consistent estimation and valid inference when performing regressions on data with differing levels of granularity

Imagine that a dataset has a combination of variables of differing levels of granularity (e.g. an international sample of firms containing both firm-level and country level information). There are $K$ ...
34 views

Sum of two dependent normal random variables is not necessarily a normal

Let $X\sim \mathcal {N}(0,1)$ and $W\sim \mathrm{Bernoulli}(\frac12)$ be an independent random variables.Define the random variable $Y$ as a function of $X$ and $W$  Y= h(X,W)=\left\{ {\text{X, if ...
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Training Neural Network with Simulated Annealing

I am trying to train a simple neural network with simulated annealing. I have programmed a neural network with an input layer of 784 input nodes (28 x 28 pixels, I am using the MNIST database to train)...
27 views

Show statistical significance (or not) between means

Suppose I have two experiments A and B. Each experiment is composed of N elements that are clearly separated into two groups. In experiment B one of the groups has a higher mean than the same group in ...
24 views

Appropriate model choice for analyzing a cluster based longitudinal randomized controlled trial

I am performing a randomized controlled trial (RCT) of an educational intervention to improve knowledge, belief and practice among healthcare workers in hospitals. One hospital is assigned to the ...
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sample size to detect variability in a sample

I have a sample of continuous data which I use to build a random forest model. Now I want to determine, how many additional samples I would need to improve the prediction (reduce the RMSE by a certain ...
20 views

Unusual Markov inequality for normal distribution

I'm trying to answer the following question from Larry Wassermans book on statistical inference. My question is how did they arrive at the Markov bound, it does not seem like the normal form of the ...
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On an alternative filter for a particular class of state space models

Let $\{ X_t \}_{t \in \mathbb{Z} }$ be a real valued time series that can be represented in a state space form, in particular assume that the sequence $\{ X_t \}_{t \in \mathbb{Z} }$ satisfies an ...
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Enforcing Dirac delta-like Activations on a Neural Network

I am working on a custom neural network model including convolutional and dense layers. I intend to enforce outputs a certain dense layer to approximate a Dirac delta function (or any localized pulse)....
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A Strict Sense Stationary (SSS) process implies it is a Wide Sense Stationary (WSS) process - proof

Looking for a mathematical proof which shows that a Strict Sense Stationary (SSS) process is necessarily a Wide Sense Stationary (WSS) process.
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Data Analysis using SPSS in Chi-Square Test [on hold]

I want to analysis newspaper contents using the Semetko and Valkenburg (2000) five news frames. Please which is the best statistical analysis to use in conjunction with the chi-square test. can ...
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Binary text classification with a variable amount of documents per labeled datapoint

I have a dataset with a label TRUE or FALSE for each person, but each person has multiple documents associated with them (emails ...
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Recognizing whether a written and spoken number is the same

For our ML assignment we have three datasets. The challenge is about checking whether a written and spoken number refer to the same number. We're using the MNIST dataset with handwritten numbers, and ...
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gogarch package

I have read the description to gogarch package, but i don't understand the function of external.regression option in that package.. How it is working ? could you give an example? ...
14 views

Lasso, ridge and elastic net regression using package h2o [on hold]

So basically when fitting a lasso estimator and ridge regression, all variables are kept in the model(none of them are shrunk exactly to zero). Now for ridge this is normal, but for lasso some of them ...
10 views

why is VAE reconstruction loss equal to MSE loss

At which situations does reconstruction loss of VAE equals MSE loss between input and reconstructed output? Other answers where not complete!
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How to calculate a permutation confidence interval?

Mara Tableman, Minh Nguyen, and Michael D. Ernst note The idea behind a permutation confidence interval is well known and fairly straightforward (Ernst 2004). The confidence interval is simply the ...