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A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more random variables. The model is statistical as the variables are not deterministically but ...

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Trying to run a hierarchical ESEM in MPlus 6 [on hold]

I've been trying to run a hierarchical ESEM using MPlus 6. Running the first-order ESEM works fine (see below for that example). But when ever I try a different method to add a general factor in to ...
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Modeling based on certain constraint

I am dealing with a dataset that contains exactly one dependent variable $y$ and 5 independent variables $x_i:x_1,x_2,x_3, x_4,x_5$. My goal is to find the best combinations of $x_2,x_3, x_4,x_5$ ...
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1answer
30 views

What does it mean to model data as binomial?

On Wikipedia it says [T]he binomial distribution with parameters $n$ and $p$ is the discrete probability distribution of the number of successes in a sequence of n independent experiments, ...
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How to deal with standard deviation of experimental data in ABC

I have experimental data points with standard deviations. How does one weight the contribution of each approximation of a parameter using ABC based on how large the SD values are of the experimental ...
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11 views

How to specify a scaled-t family in brms (R)?

I built a model with the gam function from MGCV using the scat family because my Y variable is heavily tailed (https://rdrr.io/cran/mgcv/man/scat.html). The residuals of the model are fine, and almost ...
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Which model to use to predict if a tag is gonna change over time

I'll try to explain my problem as best as possible: my data is a six month long time series. My data tells if an employer paid each of its employees taxes. Every tax month is associated to a ...
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3answers
124 views

To overfit, or not to overfit, that's the question

I hope this is not a stupid question. Let us say I have a data generation process that is quite stationary and I do not care about arriving at generalizable knowledge but more about accurate ...
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8 views

ARCH effects on my VAR fit

I am estimating a VAR model to later understand the relationship between my physical prices and financial prices (I am working on commodities). I have followed the procedure below but I am not sure it ...
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14 views

How to implement Bayesian Information Criterion (BIC) in a practical problem?

I found a lot of theoretical literature about BIC online, but I had a difficult time when I was trying to find a real case. So I was wondering how do we implement the BIC in a practical problem? Do ...
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6 views

Staticially comparing Error of two Distributions

I have a model that generates a probability distribution Sum(p(1),...,p(n))=1 I have the ground truth, again p'(1),...p'(n) Their difference I defined as the error/variance. I have a random ...
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1answer
26 views

My deep learning model works with Stratified K-Fold, but not in predicting future time events

I have a project at work where I'm supposed to predict a specific location given cell phone signal parameters. I developed a deep learning model that uses convolutional neural network on time-ordered ...
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16 views

Modelling and Variable Values

I'm trying to estimate labor demand of two different groups, using a panel dataset which consists of $\ N$ industries and $\ T$ years. Assuming heterogeneity among industries, my tentative econometric ...
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45 views

Using Gamma-log link GLZM for non-normal data?

My college supervisor for Psychology has advised me to use a GLZM (gamma family with a log link) to analyse my data set, on the basis that the response variable is 'all positive data, and is 'right-...
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10 views

Truncating covariates if linear relationship breaks down for large values?

Suppose you fit a model $$y_i = \beta x_i + \epsilon_i$$ Where you strongly believe this linear relationship holds for the vast majority of observations. Suppose, however, that a small number of ...
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24 views

Modeling using Time Series Data

Thank you for reading. I am interesting in taking historical data in the form of a time series and modeling it using OLS and other regression techniques. I am not interested in forecasting the time ...
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1answer
38 views

Smoothing in Time and Space, with Random Effects

Setup My city has recently run a pilot program to mandate that only public transportation use particular sections of the downtown core. The city has released data about the program. They have ...
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8 views

fitting for random remnants of known perturbers

I have the following problem: We try to analysis spectra. In our data analysis, we have to correct for perturbers that occur always at the same frequency and can be approximated by a Gaussian of ...
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1answer
23 views

survival analysis without censoring - time dependent features and missing values

I came across this: Time to event with no censoring - use survival or normal regression? which answers the subject (question). However, I am also wondering, is survival analysis not also the only (?)...
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1answer
42 views

Linear regression model, SCE,SCT,SCM and model's error

Could you please check if what I've done is correct? and how could I improve some of them? Thank you in advance. Suppose I have the following data (the original data its like 20 data with decimal ...
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1answer
21 views

Separate Models vs Flags in the same model

I have customer data from 2 brands. The data structure are the same, but I expected the customer behaviour to be different in different brand. So I could train 2 models, 1 for each brand, or I could ...
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10 views

Correct classification of function of four-point trajectory

This graph depicts the output of group-based trajectory modelling (generated using the 'traj' plug-in in STATA). Strangely, the model has the highest AIC when all three trajectories are defined as ...
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1answer
30 views

When and how to use withSampW in the function get.weights of the Package twang?

I am using Twang R package in my analysis but I have doubt as to when and how should I use or not use the function get.weights. The package documentation here and ...
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Electrical Load Profile Data - How to think about problem Statistically

I have a couple of time-series data sets. The Time series is 30min values for 2016, 2017 and 2018 for the following: (30 min integrated kW Values, 48 per day) Supply points x 10 for 2016, 2017, 2018, ...
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Sensitivity analysis of a model with parameters as percentages

I have the following method to calculate sensitivity above and below a parameter's reference value: Splus = (Cplus – C) / (dP/P) & Sminus = (C – Cminus) / (dP/P) Let P be the parameter whose ...
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1answer
45 views

EM Algorithm and Pattern Mixture Modelling - Is this a correct understanding?

I'm quite new to both the EM algorithm and pattern mixture models (for NMAR data). I am hoping someone can confirm my understanding is correct, and if not, let me know how to do it correctly. The ...
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2answers
88 views

How to combine properties of different functions into a new function?

The logistic function has the differential equation: dy / dt = ky(1 - (y / L)) Solving this differential equation by separation of variables and integration yields the Logistic Equation: f(t) = L / ...
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What is Gamma model?

Recently I saw a person's resume online and it is said he used ARMA and Gamma model to analyze time-series pattern of bond market volatility.I know what ARMA model and Gamma distribution is but not ...
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1answer
27 views

What is the correct distribution of reading time for short text

A mobile app I am creating shows a sequence of headlines which when tapped on shows more detailed information. The detailed information can belong to one of several, but small, categories and has a ...
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1answer
47 views

how to choose model when training accuracy is lower than validation accuracy while training neural network?

Below is a specific case but a general situation i find myself involved with in my job. This question is intended at getting ideas on how to pick the best model: Dataset: rows: 10,166, features: ...
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14 views

What is best method to calculate customer lifetime period?

I've tried to predict customer churn and i get good accuracy score. Now what im trying to do is predict customer lifetime period. My dataset has customer lifetime period information as months next to ...
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58 views

Comparing 2 Bayesian Models with different structure

I'm a bit new to Bayesian statistics so please bear with me if this question is trivial. Let's say I have $100$ observations for $2$ Bernoulli variables $X$ and $Y$. I notice that they have the ...
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10 views

Is it possible to store KNN data imputation as a model so the dataset doesn't have to be used?

I want to create a program that will use KNN method of data imputation to fill in missing values. I don't want to ship a dataset with the program just so it can use it to impute the values (data ...
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11 views

Geometric Mean Bias result for air quality models

i'm calculating the Geometric Mean Bias (MG) for the results of an air quality dispersion model against observations with the following equation from Chang and Hanna (2004); $MG = exp(\overline{LnC_o}...
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Evaluate a method taking into account when it fails

I am performing a grid-search (looking all/many variations) of a hyperparameter X to find the optimum value of that parameter. Where X is a symmetric matrix, where I set different values in each ...
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i-th attempt in drawing a question from a set of Multiple-choice questions

I have a training set with $n$ records. For each record $(x_i, y_i)$, $m_i$ questions are drawn from a question bank with $p$ questions. Each question $j$ is a multiple choice question with $q_j$ ...
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Analysing pre-and-post intervention study with anonymous responses

The study I am analysing is a pre-and-post intervention questionnaire of students' views before and after studying a module. The questionnaire was distributed in three different geographical ...
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43 views

Unofficial Google data science blog problem application

Problem description: Every 3 weeks a fashion company sends out an expensive booklet with descriptions of clothes to each customer from the company's electronic records. There exists a purchase history ...
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Statistical model choice for historical elections?

I'm interested in exploring the effects of changes in voter turnout on historical elections. (For example, how would voter turnout have had to change for candidate X to win a senate seat in 2008 ...
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1answer
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Systematic way to determine if a model is linear or nonlinear? [duplicate]

Determine whether the following models are linear, intrinsically linear, or nonlinear (disregard the error structure): $y=\beta_0+\beta_1 x_1 +\beta_2 x_2^{\beta_3}+\epsilon$ $y=\beta_1 + \...
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1answer
51 views

Advertisment decision making based on customer past behaviour

Problem description: Every 3 weeks a fashion company sends out an expensive booklet with descriptions of clothes to each customer on their electronic records. There exists a purchase history what each ...
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254 views

What is the actual significance of a difference in AIC or BIC values?

Usually, when a difference of a statistic is discussed, that discussion is presented in the context of a significance of that difference. When self-entropy, i.e., information content, is examined, ...
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1answer
23 views

Categorical Variables in Random Forests

I am aware that categorical variables should be one hot encoded before modeling with random Forests. But I am not entirely sure why. Lets say we have a predictor categorical variable with 7 levels. ...
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Closed form solution for a Zero-Truncated Negative Binomial Exposure Model

First, here's a example of the problem I'm trying to solve: Let's say my data is the total number of times that a patient was visited by a doctor while staying at the hospital. It's count data (...
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Is it possible to “tune” a trained model in one population so it can be used for a different population (i.e., by swapping variables)?

Say, I have trained a model to classify patients into cardiovascular disease (CVD) and non-CVD. The model building process is as follows: There is a gold standard to compare the model with. The ...
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1answer
29 views

Is the sum of non-identical zero truncated Poisson random variables also described as a zero truncated Poisson?

The sum of Poisson distributed random variables is itself Poisson distributed. Does this hold true for the sum of Zero Truncated Poisson distributed random variables?
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How do I check whether two variables overlap in the information they contain?

I'm looking for a method to determine whether two variables contain the 'same' information. The information I'm using has different types of 'missings' or special meanings represented by specific ...
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1answer
37 views

Statistical Modelling of a complex experimental design

I have the following experimental design, and am quite uncertain which statistical approach would be the best to investigate my data. I have three experimental treatments of my participants and would ...
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6 views

Formulating model to measure the recency (in time) of a random variable

I run a social news ranking web application (built in Python) where users post items and vote on others' such postings. I am trying to curtail Sybil nodes so that disingenuous voting can be rooted ...
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How do i compare two related time series data sets?

Generally I have two time series data sets that are potentially physically related. The data sets are in the form of xy pairs of time and pressure. Generally the pressure will go down but will have ...