Questions tagged [model]

A formalization of relationships between stochastically (randomly) related variables in the form of mathematical equations. DO NOT USE THIS TAG BY ITSELF: always include a more specific one.

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Definition and delimitation of regression model

An embarrassingly simple question -- but it seems it has not been asked on Cross Validated before: What is the definition of a regression model? Also a support question, What is not a regression ...
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Should covariates that are not statistically significant be 'kept in' when creating a model?

I have several covariates in my calculation for a model, and not all of them are statistically significant. Should I remove those that are not? This question discusses the phenomenon, but does not ...
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When forcing intercept of 0 in linear regression is acceptable/advisable [duplicate]

I have a regression model to estimate the completion time of a process, based on various factors. I have 200 trials of these processes, where the 9 factors being measured vary widely. When I perform a ...
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Mixed Effects Model with Nesting

I have data collected from an experiment organized as follows: Two sites, each with 30 trees. 15 are treated, 15 are control at each site. From each tree, we sample three pieces of the stem, and ...
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Why should we use t errors instead of normal errors?

In this blog post by Andrew Gelman, there is the following passage: The Bayesian models of 50 years ago seem hopelessly simple (except, of course, for simple problems), and I expect the Bayesian ...
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Is R-squared truly an invalid metric for non-linear models?

I have read that R-squared is invalid for non-linear models, because the relationship that SSR + SSE = SSTotal no longer holds. Can somebody explain why this is true? SSR and SSE are just the ...
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Which model should I use to fit my data ? ordinal and non-ordinal, not normal and not homoscedastic

Here is the kind of data I have: I have two predictor variables: discrete non-ordinal --> c('a', 'b', 'c') discrete ordinal --> ...
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How can you account for COVID-19 in your models?

How are you dealing with the coronavirus "event" in your machine learning models? Let's say you used to predict the number of sales each month. The virus affected your results last year and ...
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The difference between with or without intercept model in logistic regression

I like to understand the difference between with or without intercept model in logistic regression Is there any difference between them except that with the intercept the coefficients regard the log(...
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Should I remove non-significant variables from my regression model

I have run a multiple linear regression using stepwise regression to select the best model, however the best model returned has a non-significant variable. When I remove this the AIC value goes up ...
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Interpreting the regression output from a mixed model when interactions between categorical variables are included

I have a question about my use of a mixed model/lmer. The basic model is this: lmer(DV ~ group * condition + (1|pptid), data= df) Group and condition are both ...
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In layman's terms, what is the difference between a model and a distribution?

The answers (definitions) defined on Wikipedia are arguably a bit cryptic to those unfamiliar with higher mathematics/statistics. In mathematical terms, a statistical model is usually thought of as ...
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What is a 'true' model?

A short question, but I am somehow unable to find any concrete answer. I suppose it means that the model is as good as it can be? Containing all relevant variables and hence not suffering from any ...
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Coronavirus growth rate and its possibly spurious resemblance to vapor pressure model

I collected the latest data on the coronavirus from Johns Hopkins University as shown and fitted different curves to this data to model the relationship between the number of confirmed patients $P$ ...
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Is an overfitted model necessarily useless?

Assume that a model has 100% accuracy on the training data, but 70% accuracy on the test data. Is the following argument true about this model? It is obvious that this is an overfitted model. The ...
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Fitting exponential decay with negative y values

I am trying to fit an exponential decay function to y-values that become negative at high x-values, but am unable to configure my nls function correctly. Aim I ...
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Cox Model and proportional hazards

I'm trying to fit a Cox model, but there is some problems. I have the following variables in the model. Group: 1, 2, ..., 9 Sex: 1 female and 0 male Weight Age The first thing that I did is split ...
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