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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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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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34 views

Mathematical equation [on hold]

I did a Poisson model and wanted to create symbols something like the example below However, I could not personally create my own version of the mathematical symbol because I am not familiar with ...
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7 views

Could a synergy be statistically measured by multiple mediation analysis?

In order to measure multidimensional effects, it can be common to compute a score, as a combination of unidimensional factors. For instance, one could compute a score ...
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28 views

How to statistically model this?

I am studying if men and women consumers differ in how attractive they find product advertisements written differently. I am specifically looking at positive and negative sentiments as two ...
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1answer
25 views

Is it class imbalance? Test set gives very high proportion of a class which was in minority in train set [closed]

I want to investigate why am I seeing the below described phenomena. I welcome all the logical explanation which might hint towards what is happening. So I have a dataset which contains two classes: ...
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7 views

Adding Denoiser to Existing Autoencoder Network

I currently have implemented a Machine Learning Model that is very similar to the model proposed by this paper. It works pretty well on the data I have, although sometimes the training goes awry and I ...
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22 views

Sufficient statistics and wrong model assumption

Given any model for the underlying probability distribution $f(\theta)$, sufficient statistics provides us a way to estimate the model parameter $\theta$ with confidence without wasting the sample ...
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2answers
45 views

Weighted linear regression from log-likelihood?

I have 500 time-series and for each one, I compute the best (aka max likelihood) parameter α in a model that I'm testing, along with the corresponding log-likelihood. Now I wish to uncover a linear ...
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10 views

which recall value to plot for same precision in PR curve?

Suppose, after sorting the true labels by the corresponding classifier scores, we obtain the following: $$[False, True, False, True, True, True, False, False],$$ which leads to the following points ...
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25 views

Temporal Difference Modelling

I am a student who is attempting to pick up the logic of Temporal difference learning to model fear conditioning. At the moment I have understood the main update procedure $$VS(t) = VS(t) + a(r(t+1) + ...
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1answer
51 views

Can a logistic regression have both continuous and discrete variables as covariates or as regressors?

My dependent variable should be binary, but can I include discrete and continuous variables simultaneously in my equation? For example let's say X1 is discrete and X2 is continuous?
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0answers
24 views

How to refine a logistics population model? [closed]

I have to refine a logistic population model so that it more accurately fits a set of data and was wondering how to do this. The only way I can find is to use a variable carrying capacity however I ...
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1answer
20 views

Regression kNN model vs. Classification kNN model

I was wondering what is the difference between regression kNN model and classification kNN model. I tried Googling and no success. In presentation from lectures we only have graphs of errors of ...
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20 views

Is a three-level multilevel model appropriate for my research question?

For a study that is currently in the planning stage we are considering what kind of model would be most appropriate. We are interested in the interactive effect of a drug (vs. placebo) and hormone ...
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20 views

GWAS: how do we know we have the most appropriate model?

[Note: crossposted on Biostars here] My question is about how to know when the optimal statistical model has been selected for a GWAS (genome wide association study). I appreciate that statistical ...
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1answer
18 views

Framework for reducing the dimension of the features of multiple correlated Time Series with a notable amount of memory

I have a dataset that I am trying to analyse that consists of multiple (~500) time series each with around 25 observations. For each observation I have a large number of covariates, some of which will ...
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18 views

Soccer Attacking And Defensive Strength Using Maher's Model

I have read the paper by Maher which talks about modelling football (soccer) score. He uses parameters like alpha, beta, gamma and delta for attacking strengths and defensive weaknesses (both home and ...
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13 views

Compare QICC for two non-nested GEE models

For my thesis, I need to compare two non-nested GEE models. As the models are non-nested I did not use Wald chi-square, instead, I calculated QICC to compare the goodness of fit. The difference ...
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6 views

Acceptance rejection with Halton sequence as RNG

I am coding various normal random variable generators, one of them being the acceptance rejection method: ...
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1answer
17 views

Manga translation updates: what kind of data/what model?

Long story short, I'm trying to predict how likely it is for a content creator to release new content or when they are most likely to do so (and possibly how this changes over time). My problem is ...
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11 views

Using the Volume of Sales obtained today to predict volume of Sales at the Event

I wonder if anyone can help. I have a set of data on event ticket sales. I have information on eventdate, location, capacity, cumulative sales, sales date, total sales. I want to be able to build a ...
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0answers
13 views

Bootstrapping quantiles from an estimated binary outcome

I am trying to predict a binary outcome that is unobserved but I have made bootstrap estimations of its value. As a result I have bootstrapped training data where the outcome for the same observation ...
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1answer
30 views

Interpretation of regression coefficients with different subsets of independent variables

I have a multiple regression problem. Let's say there is a physical system with a true model: $$ y = b_0x_0 + b_1x_1 + b_2x_2 \;\;\;\;\;\;\;\;\;\; (1) $$ Now, imagine I only have access to a ...
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1answer
40 views

How Can Poisson Regression Predict a Count of Zero? [duplicate]

I am reading "Modelling Count Data" by Hilbe and I feel I am missing something fundamental about Poisson Regression. $\hat{\mu} = \exp(\alpha + \sum\beta_ix_i)$ One of the requirements for using it ...
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26 views

Fitting a system that transits between two time varying states

I have a system that transit between two different states. Each state output varies linearly with time, given by m*t+c, where both lines intersect the x axis in the same point. The output of this ...
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37 views

How people use Stacking method in the real-world problems? [closed]

I know that stacking is a very strong method when you using it in machine learning competition(Like Kaggle). But in real life situations do people use this for modeling very often? I heard that ...
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23 views

Statistical models of metabolic pathways

I would like to use cross-sectional data to test an hypothesised metabolic pathway, for example like this: My dataset includes data on A and X, and some - but not all - of the other intermediates. ...
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7 views

Parameter estimation for NHPP for arrival series

I have multiple data sets (about 15) that describe a process of arriving customers to a shop. When plotted it's pretty clear that over time the rate of customers arriving decreases. However the time ...
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16 views

How to test null hypothesis of “observer A sights animal at the same time that observer B sights animal”

I have 2 observers at different platforms making sightings of animals in the wild. Observers work independently of one another. Observers record when an animal was sighted, as well as the location of ...
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12 views

How to interpret regression results when there are categorical independent variables? (statsmodels | python) [duplicate]

I'm using a toy dataset from sklearn and adapted it for a linear regression framework. In this example, I'm constructing a ...
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4answers
115 views

Is it acceptable to scale a model based on “intuition”?

Suppose that a model has been produced that will predict the total number of customers in a business. You are generally happy with the distribution of the model and believe the trends shown by the ...
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1answer
31 views

What to do when the test data set has many “features” that are generated by dummfying a categorical variable that are not present in the training set

Say you have a variable (in this case industry) that you dummify (one hot encode) hence creating many new features in both the training and test sets for which you are getting ready to run a machine ...
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1answer
22 views

Should I use the results of a previous model in my second model?

So I've been trying to predict a minority class, and thus far I've built an svm/boosted tree/random forest/logistic regression/knn combo. After making them all and tuning them and doing feature ...
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33 views

glmmTMB in R beta regression or Poisson distribution?

I have a data set which is very zero inflated. Zeros are representative of true zeros, meaning that in this case a zero is a legitimate value to have indicating something about the individuals tested (...
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39 views

Help interpreting an interaction term from R output of linear regression

So I am familiar with the concept interaction. However in most instances that I have come across, a significant interaction term is in the same direction as the 2 individual terms. However I have come ...
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1answer
13 views

Measure how representative a feature sample is of the feature space, and the effect on statistical significance

I may not be asking this question correctly, but my curiousity concerns separating the statistical significance of sampling about features (as opposed to whole samples), how to measure this, and how ...
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13 views

What is the appropriate model for data with a 1:n response to independent variable ratio

I suspect I am at a loss of terminology, and will accept "Google search terms [x, y, z]" as an acceptable answer in this case. The nature of the process being observed is as follows: a certain Goo ...
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3answers
57 views

Why is the price of a security after $n$ intervals of additional time modeled using a lognormal distribution?

I am reading a book about financial mathematics. There's a problem in the book that says that if $S(n)$ denotes the price of a certain security at the end of $n$ additional weeks, we can model the ...
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8 views

Specification of partially nested / partially crossed longitudinal 3-level model

I am analyzing how properties of brain hemispheres change over time under different conditions. Each subject has a left (L) and a right (R) hemisphere for each of which I measure the property of ...
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2answers
42 views

Using a predicted value as independent variable in a regression analysis

I know that a certain percentage of error already exists in predicting a measure (ex.: lean body mass) and predicting a cardiorespiratory parameter such as Vo2max using this predicted measure only ...
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1answer
32 views

Referring multiple names to the same entity

I am working on the models of different product types and wish to generalize them to the same entity. For example, from the given list ...
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1answer
21 views

Calibration of an individual-based model of an epidemic

I am currently developing an individual-based (or agent-based) mathematical model (IBM) of an epidemic. I want to calibrate the transmission parameters in my IBM to match empirical data (epidemic ...
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17 views

What statistical method should I use to analyse data with 3 random variables and 2 fixed variables ? Their interaction is also important

I had 7 treatments for my experiment (where each treatment had a specific type of pesticide) including A, B, C, a combination of A&B, a combination of A&C, a combination of B&C, and a ...
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25 views

Endogeneity and variable development

Basic endogeneity question here: I'm estimating a standard migration model, with the household ($i$)'s decision to migrate ($m_{iv}$) as a binary dependent variable , using cross-sectional data: $...
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24 views

Fitting a reinforcement model to reaction time

I have a data set of reaction times in a simple reward/punishment task, in which the rate of feasible trials is probabilistical (around 2/3). After having a look at the reaction times, it seems ...
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27 views

R - outliers with complex data

By now I'm convinced of the importance and improvement gained when using the robust packages (ex: baserobust) to fit data. I've use it both for linear and non-linear fitting with some degree of sucess....
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22 views

Best methods for gaining insights (drivers in my data) searching for patterns

I want to analyze website data (e.g. every event that a customer took on our website, is captured in binary data (Yes/No). The target is if a visitor bought something on our web shop. ...
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1answer
29 views

The Case of M and W: How To Model This?

A man (M) and a woman (W) meet each other at an online dating website. They begin to date. After a year, M remembers that his account at the dating website is still active, and wants to delete it. So ...
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1answer
22 views

How do I use regression to model 3 IVs and 1 DV? [closed]

I'm trying to study electromagnetic braking. I have 3 Independent Variables (different factors affecting the force exerted on a conductor moving through a magnetic field) and the dependent variable (...
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25 views

GLMM with weights or beta regression for dealing with proportions?

I have a response variable of proportions representing the number of hours an individual is performing a specific activity divided by the total number of hours in the study period. I have no 0's or 1'...