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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Building model for SEM: the problematic of highly correlated variables (SEM + Covariance)

I have recently come across articles suggesting we should avoid conducting SEM when variables are highly correlated. I have a model in which X1 and X2 predicts Y through M1 and M2. Which gives me the ...
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How to create the fixed effects model from the data? [closed]

I am working on the data about student's exams scores measured depending on techinque and the day exam was taken. ...
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Model simplification in SPSS [closed]

can someone please guide me with performing model simplification with steps in SPSS? I am assessing the attitude of people towards animal welfare and have collected data on attitudes using a Likert ...
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How should vector notation with multiple indices be interpret?

This is a question about the interpretation of mathematical notation in statistical models. Let's say that this equation represents a panel model: $y_{it} = \alpha + \boldsymbol{\beta}' \mathbf{X}_{it}...
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Validation Loss for my binary image classifier model is increasing. how to bring it down? [duplicate]

I am new to the domain of Deep learning and I have been trying to create a binary image classifier using a dataset which I created by myself. I am building the model from scratch. It is CNN model. ...
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Design loss function for model-based reinforcement learning

I'm doing some model-based reinforcement learning, and I'm stuck at how to better design the loss function for fitting the dynamic model of the environment. In continuous state and action space, the ...
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Learning Average Dependent 0/1 Variable

Suppose I have a matrix $X$ and a dependent vector $y$ whose entries are each in $\{0, 1\}$ dependent on the corresponding row of $X$ Given this dataset,I'd like to learn a model, so that given some ...
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What is the intercept in a regression model with demeaned dependent variable?

Suppose you have a regression model $\tilde{y}$ = $X\beta$ + $\varepsilon$, where $\tilde{y}$ = $y$ - $\bar{y}$ and $X$ contains a constant. If you estimate the model by OLS, does the estimated ...
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Question about understanding Weights of Keras LSTM model

I am implementing Federated Learning (FL) using Keras LSTM. Starting with the simple example where multiple models are trained at different clients. Each client shares their model weights with the ...
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What is the interpretation of the varImp() function

Computing the variable importance of different types of models with varImp(model), the obtained results are as follows: ...
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Metric that quantifies 0-centered error throughout the entire range of the data?

Say I am selecting between models, and I especially value mean-0 error throughout the entire range of the data. I am looking for metrics that specifically capture this property. For example, take the ...
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EDA with Data Modeling

After I read R for DataScience and ggplot2: elegant graphics for data analysis, I am learning how use modeling techniques to improve my EDA. I applied this on two notebooks (https://www.kaggle.com/...
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Convert a Variable based on a Chi Square Function

I have a variable Average Days Between Purchase (ADBP) on the x-axis for a given customer. Based on this variable I wish to score my customer, but the relationship between the score and the variable ...
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Comparing RMSE/MSE of original data and log10-values of the same data

I want to see if my models work better on the original data or on log10 transformed data. But how can I do this? Normally I train the model, calculate the RMSE/MSE on the test data and compare these ...
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Big NN vs Ensemble of Small NNs

Assuming the cost of training these models isn't an issue, is it advantageous to model data using an ensemble of "shallow" neural networks over a single deep neural network? My thoughts ...
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Cross Validation after using train-test to decide optimal algorithm to use?

I am interested in training different algorithms on a data set and observing performance metrics. Currently, my approach is to train different algorithms on train data, and then evaluate performance ...
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Using Rasch estimates in models

I am just starting to learn about Rasch analysis, but there is something I am a little confused on. So let's say you conduct an analysis using a rating scale model for some Likert scale and everything ...
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How to overcome Ramsey Reset test without failing in R?

I have a simple linear model with some independent variables including dummy variables for world regions. Unfortunately, the Ramsey Reset test in R rejects the null hypothesis that the model is ...
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REML for multilevel modeling comparison

With the very same data, I want to compare the two multilevel models. (these two models differs in both fixed and random effects) so, I am planning simulation study. I will generate the data set, and ...
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Linear Regression Analysis where both independent and dependent variables are binary indicator variables - Interpretation/Model

I trying to model the probability of a women having received a mammogram in the past year (MAMHAD1YR). This variable is 0 or 1. Where 1 indicates that they have received a mammogram and 0 indicates ...
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measure of association between dichotomous variable and non -dichotomous (category of 5 levels) while correcting for multiple confounders?

I have a data with 2 groups (fit/healthy) and dietary intake data as ordered categories (less frequent to more frequent as 1,2,3,4,5). I have to assess the relationship between the groups and the ...
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Accuracy failure example

I am trying to understand the functioning of accuracy and I need a practical example. This is what I understood: it gets the average correctness of the predictions and in some cases its result can be ...
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Methods for selecting the best variable into the regression model

I have constructed a continuous variable by using two different methods. Now I want to know the variable created under which way is the best and should be included in the model. Some preliminary ...
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What is the meaning of mean reverting level and what this metric tells us?

I was modelling an ARMA process of the Unemployment rate of the USA and I was required to calculate the mean reverting level of the model. I chose the following model: ARIMA(1,0,2) (The data was ...
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Develop a Situated Learning model

I shall be very thankful for this act of guidance, very much confused about the things. My thesis topic is "Development of situated learning model with respect to community project carried for ...
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When to what when building a linear model?

There a many tools to building linear models, such as adding non-linearity, adding splines, adding interactions, variable selection. It can feel overwhelming when considering all of the options… For ...
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Which best model I have to use to calculate standard deviations?

Suppose that I run the same experiment 5 times. Now, suppose that each model of each experiment has the best accuracy in different epochs. For example: Model1: best accuracy after 10 epochs Model2: ...
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Best approach for AIC model selection?

I am doing a study where I am trying to model how different factors affect polar bear movement. I would like to conduct model selection using AIC. So far, I believe I have two options:   1)    Put ...
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Should I use GLMM or GAM in my analysis?

I am analyzing data on polar bears and trying to figure out if different variables influence their movement. My data has a mix of categorical (e.g. bear ID number) and numerical variables (e.g. bear ...
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How would we define a "model" in terms of its relation estimators and statistics?

I found this to be an interesting post but I want to hone in on the definition of a model. It defines a model as: the function (or pooled set of functions) that you may accept or reject as being ...
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Can the term 'hyperparameter' apply to non-ML modelling?

Commonly when modelling biological systems, some parameters may be from elsewhere or previous modelling fits, and are not being investigated in the current model. These seem to be equivalent to the ML ...
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Validity of external cross validation using data generated by the fit model?

Context: A paper I'm reading uses PDEs to characterise the effects of cancer treatments on the tumour microenvironment. The exact wording used in the paper is: The predictive power of the [...
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Problem formulation classification task

I would like to know if it is correct for a classification task in a supervised learning to say the model we are looking for is a function from RxR to a discrete space $$ f:\mathbb{R}\times\mathbb{R} \...
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comparing data regularity

I have data about ratings from 5 sessions, it appears that initially ratings are random, and with experience, they become more 'defined', settling into a pattern (see graph below). How can I test this ...
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model to explore correlation of pollution long-term exposure with genetic mutation rates

I have pollution data of several US cities, as example NY, Boston, and Chicago. I need to ...
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Is there any theory or field of study that concerns itself with modeling causation rather than correlation?

My understanding is that probability (at least from a frequentist viewpoint) is a mathematical tool for modeling correlations. So, for example, we can say that two events $X$ and $Y$ are defined to be ...
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How to compare results of a discrete (binary) model to a probabilistic model?

Let's suppose I have two models that both indicate the presence of some phenomenon: Model A: Only binary results, i.e., the phenomenon is present or not, Model B: Outputs class probabilities. Of ...
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same model evidence, different MSE on the test set, which model to report?

I am using Relevance Vector Machines RVM's for regression as from: https://www.jmlr.org/papers/volume1/tipping01a/tipping01a.pdf?ref=https://githubhelp.com. My basis functions are the simple ...
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Interpret ANOVA analysis of model fit IRT, TAM Package

I posted this question on Stack Overflow, but was advised to post it here. I fitted the same data set to a 1PL item response theory model (called onePL below), and ...
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Logistic regression: Why is the reduction in model deviance greater than a univariate model, when other terms are included? [duplicate]

I have a panel/discrete time logistic model with binary outcomes. To begin the exploration, I model each variable in a univariate model and note the reductions in deviance: ...
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Can I compare the AME for two logistic regression modells?

I am using R Studio to run logistic regressions. I have a dataset, which analyses voting behaviour. I want to analyse the effect of different independent variables on the dependent variable "...
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How to get the probability a prediction is correct from a binary classifier

I have an image binary classifier that where class a = 0 and class b = 1 When I receive a prediction of a single image, is working out the probability that the prediction is correct as simple as: a: ...
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A Proper Conjugate Model for A/B Test for Revenue per Click (RPC)

What would be a proper Conjugate Posterior model for Earning / Revenue per Click in A/B test? The data is the total number of visitors and the total revenue per day per variant (A and B). What are the ...
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Improve the model performance using MLE

I have a dataset and want to fit a model to the data. In particular, I used three models and estimated parameters using MLE and found model (2) provides a better fit in the following picture. However, ...
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Do time intervals have to be consistant for a Markov chain?

My set up is as follows. I have about 50 groups of people who move about 5 states. One of these states is essentially "not-doing anything". I have their states recorded at the time-scale of ...
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1 answer
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How to identify the distribution for regression models

I am trying to analyze hunting harvest data with response-variable being individuals/1000 hectares and a series of explanatory variables to describe it. Response variable is continuous (fractionals), ...
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Random effects, single observtion mesaured multiple ways

I am constructing some binomial glmms and thinking about my random effects. Let's say I measured the number of bugs on 3 different plant types, and the abundance (relative area) of those plant types. ...
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2 votes
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Calculate predicted values after validation of logistic model

I have a simple logistic model, and I internally validated it using rms::validate in R. The estimated overoptimism for the intercept is -0.015 and for the slope is ...
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Calculating marginal effects in probit-model

Is there any literature where the calculation of marginal effects in probit is explained? I don't find anything. The only thing I found is this: How do I interpret a probit model in Stata? Is the ...
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Modeling a card game win percent as a function of deck matchup and player skill

In collectible card games like Hearthstone, players choose their deck before playing a game vs each other head to head. This is a two player game. I want to analyze this to predict the probability one ...
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