Questions tagged [modeling]
This tag describes the process of creating a statistical or machine learning model. Always add a more specific tag.
2,428
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How to incorporate data from different time periods to predict species presence?
I'm attempting to model the probability of presence of a single species, based on (WorldClim format) bioclimatic variables, using both present and past known distribution data.
I've so far created ...
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What method to find relation between variable A and B with unequal replicates in different plot
I have an experimental setting as illustrated below.
Two different set of soil variables (say A and B) were taken in multiple plots (Plot1, Plot2, Plot n, those are not properly plot maybe... rather ...
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Probabilistic Model for Planning
THE CASE:
A researcher reports of a chimpanzee in captivity filling his mouth with water in order to penalize a not-so-friendly keeper. The chimpanzee coaxes the keeper, and tries to lure him to ...
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Writing mathematical equations (mixed effect models)
I have the following model which i am trying to write the mathematical equation for.
model;
mod = lmer(test ~ IQ + ses + (1 | Class), data = pupils)
I have the ...
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Content Based Recommendation System
how will a content-based recommendation system recommend after a sudden change in taste of user??
what will the system recommend to new users without any data about them available in content-based ...
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Memorylessness by way of additional dimensions
This is a somewhat broad question that occurred to me regarding the nature of memorylessness. Namely: Is there utility in considering systems which are themselves not memoryless, but then expanding ...
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Which distribution do reddit link scores follow?
I'm trying to model the distribution of link scores (number of upvotes minus number of downvotes) on reddit, for a single subreddit at a time.
For example, here are some histograms of post scores on /...
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Post-hoc tests for unexpected outcome of binomial models
This may be too abstract for SE, in which case I will post in other forums.
I am running a binomial glm, where my response variables should be ...
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Inference Modeling for COVID Data
I am trying to build a model to analyze the relationship between COVID-19 mortality rate in each U.S. state or county (y) and independent variables (x) including:
Vaccination rate: 1st, 2nd, booster
...
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Models for testing non-linear dynamics (e.g., threshold effects), where threshold is not necessarily known
Any recommendations for models (or applications in papers) to test theoretical predictions about non-continuous effects, e.g., based on a threshold, rather than marginal effects? Some examples of the ...
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Car rental time series forecasting
I have the time series of car rentals/demand in a location. The time axis is every hour for 3 months. The y-axis is number of car rentals/demand.
I want to do prediction for future hours given this ...
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Classifying year as a categorical variable + ANOVA
I've been debating for long if year is a categorical or numerical variable (by year I mean 17 discrete values from 1925 to 1941).
I need to test if:
a) time has a significant impact on the price of ...
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Resid vs Fitted plot for similar data on lme4 model looks vastly different on similar data. Error: "boundary (singular) fit: see help('isSingular')"
Forgive me if I am missing important information this is my first time posting here. I am trying to build a mixed model to see effects of a management treatment (gridtype) on body condition of certain ...
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Ordinal Regression: Significant p-values and no colinearity, but very high misclassification error
I cannot show the R code, since it is about a confidential research project. I hope someone can still help me make sense of this.
I conducted ordinal logistic regression with a few ordinal, discrete, ...
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Does the assumption of “independent and identically distributed” apply to the actual sample data or the sampling process?
While studying statistics, I came across the concept of “independent and identically distributed random variables” or IID.
I’m confused as to what that applies to in practice, mainly, does it apply to ...
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Are "weights", "loading scores", and "singular values" all synonyms?
I'm currently learning to use "eigenfaces" for facial image classification. Unfortunately, I've encountered some confusion with the following lines of code:
...
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Help with a generalized linear mixed effects model of a forestry trial
I am having troubles coming up with the proper statistical model and R code for a forestry trial we did several years ago. We looked at whether wood piles left over in clear cuts were beneficial for ...
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How to simulate events in certain time?
I am trying to make simulation, and I have some events that happened durring a day. Some times it s for example few events durring half hour for one day, and sometimes we have event, and then few ...
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Recurrent event analysis: What approach to choose?
I am trying to examine if the interval between recurrent suicide episodes becomes shorter over the course of repeated incidents. My data is in long format with each participant occupying multiple rows ...
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Chi-Square Difference Test for Nested Models with a Continuous Outcome
Apologies if this is a very basic question - I'm still definitely a beginner when it comes to statistical tests. I understand that chi-square tests are conducted to determine the relationship between ...
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How to choose between one-way, two-anova and multliple regression? [duplicate]
I am working on the data set that consists of Patients' id (after stroke), Time (they can walk after going through the program), the Program they follow and the Visit number when the Time was measured....
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What is the appropriate type for the variables to be included in CART models?
I am building a CART model. However, I have certain doubts about the type of the explanatory variables to be included in the model. I ask you for your help and advice on these two specific questions:
...
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Scientific reporting of time-varying covariates at different time frequencies
Say I have the following model:
$$y_{it} = \gamma_i + \delta {T}_{it} + \zeta Z_{i(k)} + \epsilon_{it}$$
where $y$ is some outcome for household $i$ in month $t$. $\gamma_i$ denotes household fixed ...
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Combining data from multiple studies - best approach?
I'm looking at an old paper on the incidence of HPV infection by age cohorts. The authors present a plot of estimates from many different studies around Europe which looks like this - note the authors ...
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Why is non-normality of time series not a problem for ARIMA and GARCH?
My time series is very leptokurtic and non-normal, which is of course highly common for time series data. However, I don't exactly understand why that is not a problem for ARIMA modeling and GARCH ...
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Mathematic modelling vs. machine learning
As a biologist with some background in mathematics I am really interested in mathematical modelling of biological processes, like tumor development or therapy responses. However, looking at recent ...
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Data Set With Variable Start Dates for Churn Modeling (New customers from business acquisition)
I have dataset representing to specific region of the country. Its purchase data which is how much costumer is placing with associated dates of order, amount etc.
I want to do churn modeling for this ...
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Tuning ARIMA/ETS for univariate time series
I am running auto.arima/ETS models from the forecast package in R on monthly seasonal time series. I see the following fitted ...
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Can very large count outcomes be treated as continuous variables?
I have very little expertise with count outcomes and analysis of them, but I understand that, in general, they cannot be treated as continuous dependent variables for the purpose of analysis due to ...
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Constructing a time dummy variable in DiD fixed effects model
I am using a Diff-in-Diff regression design to evaluate the impact of a county-level tax hike (i.e. treatment variable) on tobacco sales (i.e. outcome variable) in a given county, relative to counties ...
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Goodness of fit for multinomials with small np
I've got a model with continuous explanatory variable $x_i$ and some positive integer $m_i$ for each datapoint, and then a multinomial response - i.e. $p$ categories, and the sum of counts across the $...
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When to square a variable (age) in a poisson regression?
I cant seem to find a clear answer to my question.
I have as a dependent variable a count ( number of times certain companies appeared in the news). One of my explanatory variables is age of the ...
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How to build a paneldata model in R?
We would really appreciate some help building regression model(s) using a paneldata set. The dataset consists of data from retailstores over two years. Our research question are as follows: How does ...
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Interpreting coefficient in a Diff-in-Diff (fixed effects model)
I am running a DiD model with fixed effects to find the causal effect of traffic cameras on my outcome variable: share of car accidents of total accidents per neighborhood.
The treatment, road cameras,...
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How to fit joint models for longitudinal and binary (outcome) data?
Joint Models are mainly viewed in the literature within the context of longitudinal and time-to-event data. For this reason R packages as JMBayes were built to fit these kind of models. Nonetheless I ...
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AUC - Logistic Regression versus LDA, and Naive Bayes
everyone!
I am a newbie on machine learning, and I am now interested on classification modeling.
I used logistic regression, linear discriminant analysis (LDA), and naive Bayes on my notebook DataCamp ...
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How to validate the decomposed distributions?
I am fitting distributions for the time spent for three processes (i.e., pick up tools, walk to destination, install) in a system that I am trying to simulate where the original data for these ...
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Which test is suitable for such data? t-test, ANOVA, linear regression?
I have data in the following format:
Concentration
speed
height
distance
control
1.5
3.1
13.1
0.1
1.9
5.4
13.5
0.2
2.3
9
16.7
0.4
2.7
13.1
21.2
I am confused as to what test I should use to see ...
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Do spatial regression models hold the assumption of linearity?
I'm running a spatial regression model (probably spatial durbin error model or spatial durbin model) and one of the explanatory continuous variables has a lot of (true) zeros. I'm worried that the ...
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Using binary dummy to control excess of zeros in continuous data
I'm running an OLS and one of the explanatory variables accounts the sewage coverage, which is zero in 42% of the observations (these are true zeros). I'm worried that the linear effect is not going ...
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Should I change the dataset to one with less zeros on the independent variable?
I'm running a spatial econometrics model and one of my explanatory variables is sewage coverage, which is 0 for 42% of the cities in the country of analysis. I've been told to reduce the focus of the ...
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How can I calculate common digits in daily numbers?
We have daily numbers with 4 digits and 3 digits. These winning numbers often,but not always, have 1 or more digits the same. It would seem there should be a strategy to calculate the percent of time ...
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Moderation-analysis with a hierarchical multiple regression analysis
For my thesis I perform a moderation analysis via a hierarchical multiple regression analysis. More specifically, I want to investigate whether closeness in the parent-child relationship is a ...
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Actual residuals versus simulated residuals for testing spatial autocorrelation
I have a dataset of observations at multiple sites repeated within and at multiple times. I need to test for spatial autocorrelation in the residuals of my model, which I have used time as a fixed ...
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When including an interaction term, do I have to put each variable separately as control variables? [duplicate]
I'm new to econometrics and was wondering when including an interaction term do I have to put each variable separately as control variables?
I know this is the case for a difference in differences.
<...
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What to do next after the sanity check i.e. overfitting over training subset?
I have two years of time-series data taken from two sensors which I have split into 80/10/10 non-overlapping train/val/test splits. The task is to denoise one sensor data into another and I am ...
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Choosing the appropriate model: mlm | panel FE | TSCS
I am a bit unsure what is the right model for assessing overtime variation with unit fixed effects, contingent on context features.
The data (n>10000) at hand consists of features of individual ...
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GLMM: X=Non integer warnings for power estimation
For starters I am both new to R and out of practice for statistics. I am going to run an experiment where participants answer a survey every day for a week, and I want to figure out the sample size I ...
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Help creating a model to fit raw data to ground truth
[Disclaimer: I searched and could not find "what kinds of questions are allowed on Cross Validated", so let me know up front if this is not the place for this question, and even better: ...
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Method to model the differences between two variables of different type using other independent variables
respondents were shown a video (chosen randomly for each respondent) of a speeding car and then asked to assess the car speed. For each respondent a set of background variables are also known.
So the ...
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