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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2 Variables, 6 replicates, Dependent Var is number of days. What analysis?
I'm analyzing # of days a particular bird species was observed in a forested area, let's say out of 100 days. I have a control plot, a masticated plot, and a burned and masticated plot. I have pre and ...
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Comparing the importance of interactions between models
I have two separate models that both use the same set of 10 continuous predictor variables.
Model_1 predicts one binary outcome (symptom_1: present vs. not present) and model_2 predicts another binary ...
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Why do we need to generate a random prediction in logistic regression? [closed]
I am trying to understand theory from my Model Identification And Data Analysis course at University.
The example I am referring to is the probability of predicting a heart attack. Essentially, from ...
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Seeking Guidance to Ecological Models: Where to Start as a New Ecology Student [closed]
I am a new ecology student and am interested in the model part of ecology. I've used a few models, and while I can get results with them, I find that I don't really understand them. I don't know why ...
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Coefficients in quasibinomial regression and model prediction plots
I'm using two quasibinomial models. In the first model, the dependent variable is the proportion x of successes in experiment A. In the second model, the dependent variable is the proportion y of ...
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Which regression model would you choose?
Which regression model would you choose to model the following flood damage data? The variables are x1=water height, x2=dike height and x3=flood damage. The following plot shows how the flood damages ...
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An independent variable that is correlated with another variable in a regression model
I'm doing a regression analysis to understand the relationship between disease severity (Severity) and viral load (VL). The <...
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Some Features are Autocorrelated; my output variable is not
I have 66 features. What does it mean if 5 or so features are highly autocorrelated (.99 at lag = 1) with themselves but my output variable itself is not autocorrelated? Can I consider these subset ...
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Can linear regressions be used? Given these diagnostic plots [closed]
I'm using several linear regressions on a big dataset (about 1000 datapoints) with one numerical dependent variable and several independent variables (both dummy and numerical):
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Can linear regressions be used, given these diagnostic plots? [duplicate]
I'm using several linear regressions on a big dataset (about 1000 datapoints) with one numerical dependent variable and several independent variables (both dummy and numerical): ...
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How to explain discrepancies between contrast estimates and mean differences?
(I'm working with R but the core of my question is about statistics.)
I'm using a quasibinomial model in R with a dependent variable and several independent variables (both numeric and dummy variables)...
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What is the consequence of not measuring time as a random effect in an MLA?
I'm conducting a multilevel regression analysis (mixed model) with time as the levels.
My teacher wanted me to measure time as both a fixed and as a random effect. However, it turned out I couldn't ...
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Creating a VAR model - data with seasonalities
I am in process of creating a forecast using VAR model for pricing of a certain commodity.
Some of my variables (such as price itself, as well as inflation, and taxation) don't have any seasonalities. ...
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Adding a categorical variable to a model fit for comparing parameter estimates?
I am fitting a non-linear model to multiples species where the y is growth rate and x is irradiance. These growth-irradiance curves are common and there is a great r package 'phytotools' that ...
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Residuals with mean 0 but with bigger standard deviation in regression
When I tried to fit a regression model to my data to predict a power variable using steam at entry and steam at exit variables in a thermal power plant, after taking care of outliers, etc... I fit the ...
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Estimation of standard deviation of the noise in simple linear regression [duplicate]
Lets Y= f(X)+ ε be our model , we assume that f(X) is linear with this form B0+B1X and ε is a random variable with mean=0 and std σ
i have read that the estimation of this standard deviation ...
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Predicting new timeseries based on related timeseries?
Let's say I have multiple timeseries, representing different features, all of length n, and I want to predict a new timeseries which represents another feature, without any past history for that ...
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Prediction intervals practical use cases in time series
i've been encountering a lot prediction intervals in regression and time series analysis to evaluate uncertainty about predictions , i'm using it in my time series forecasts , and i wanna know ...
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Longitudinal IRT model specification using MIRT bfactor function
I try to specify / calculate a longitudinal IRT latent growth model to compare learning gains between three school years in a large data set. The test were administered by a computer adaptive testing ...
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Random Walk and Moving Average for Stock Market Model
I model a stock price with a completely random walk:
In each step I multiply the price with normal distributed random number with an mean of 1.
Then I compute a signal, which is True if the moving ...
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Using bilateral export flows as a proxy variable in gravity model
I have used a gravity model (cross-section data) for my thesis and as a dependent variable, I have taken bilateral export flows which I used as a proxy to measure the risk of being exposed to a carbon ...
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comparison of generalize linear mixed effect models in R with compare_performance function
Below I add my model comparison between a random intercept and random slope model using performance library. I used compare_performance. My models are:
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What is a formal and authoritative definition of an 'assumption' in a statistical model?
The description of the tag in this website states that it
Refers to the conditions under which a statistics procedure yields valid estimates and/or inference. E.g., many statistical techniques ...
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Biphasic dose-response: what model to use in R drc() package?
I am trying to model a dose response curve that has two phases (i.e. two steps).
GraphPad Prism has the model in their workflow, but I am trying to accomplish the model fitting in R. With the ...
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Cannot apply simple OLS model in the case of low resolution devices resulting in Fourier space convolution
There's a problem which often comes up within my field and doesn't seem to be approachable analytically. Any suggestions or direction towards the class of problems this falls under would be helpful.
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Linear mixed model beta coefficient larger than one
My question is related to the linear mixed model. I have data on the built land area for three sampling sites from which we collected samples for 11 consecutive days. We collected the community of ...
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Effect of batch normalization after input layer on model performance
I built a ML model with high accuracy using
...
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ValueError while fitting a neural networks model on Consumer Complaints data
I am trying to build a keras tensorflow neural network model. I have never built a NN model prior so facing challenges with some very basic error.
I Was able to build the model using following code. I ...
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Back transforming log data
I have a dataset with biomass, dbh, height, wood density, site, and species. As data were not normally distributed, I converted biomass, dbh and wd using the log() ...
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help in Model Choosing
say i measured the same subjects, in two different times:
I measured for PB variable: which is binary: "yes", "no".
and measured their willingness to save money: which is "...
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How do I select a KNN model?
I am considering methods of selecting an optimal K Nearest Neighbors model for classifying a pixel as representing a refugee's blue tarp or not. See https://www.kaggle.com/datasets/billbasener/pixel-...
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How do I determine the output dimension of my input layer?
I'm building a keras model for a binary classification.
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Running Binary logistic regression with interaction terms vs running it on a subset of data
I am trying to run a binary logistic regression that predicts the probability of infection based on a series of categorical predictor variables, and one continuous variable.
Here is the structure:
<...
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Create different model architectures in loop [closed]
I'm building a NN using keras and I'd like to build different architectures.
My question: Can I create several models with a different number of layers at once? (e.g. using a loop).
It should be ...
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Significance test for different time series
I have two different experimental setups with three replicas each. The data describes the growth of bacteria over time. I am looking for a test to determine whether the time series of the two setups ...
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Using PCA to select best variables, and then performing Linear Regression?
I am currently working on variable selection and came accross many methods which i tested.
I tried one which i thought of, but never read about it. I would be curious if you know anything about it:
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Model to compare the methods with 0/1 outcome
I have all in all 600 measurements: 20 subjects x 15 different stimuli x 2 ears (presented in each ear separately). I use 4 different methods to detect whether there is a significant response in each ...
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Theoretical question about GAM (generalized additive models)
I'm new to GAM so please be patient with me.
This is a theoretical question rather than a coding question.
I have a model as follows:
response variable (y) = insect abundance;
Disturbance type (...
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When can we assume a particular distribution in a statistical model?
In statistics, we often assume that a particular variable follows a certain distribution. For example, if we know $Y \in \{0, 1\}$, then we can assume $Y \sim \text{Bernoulli}(p)$, since using the ...
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Cox Regression model with time-dependent covariates - violated assumption of proportional hazards (PH)
I am currently performing some Cox regression models. The image attached shows a Schönfeld residual based on one of the cox models with a significant p-value which means that the proportional hazards ...
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What is a procedure for selecting a type of logistic regression for predicting one of 5 classes based on 3 continuous predictors?
What is a procedure for selecting a type of logistic regression model (e.g., multinomial, one versus rest) for predicting the class of a pixel given its red, green, and blue intensities as in https://...
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GAM partial response plot interpretation
I've made the gam in the code below (in R), but I'm struggling to interpret the results. Specifically, the partial response plots for all but one of the variables is linear, and the CI lines cross in ...
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Fused data improve the model performance compared to models from single dataset?
I have two types of 3d scan datasets over 200 forest plots. One type of data have higher resolution (more detailed information on the landscape) than the other. I derived 10 forest metrics from these ...
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covariance terms for random effects model
I have a random effects model with two groups.
$$
y_i = \alpha_{j[i]} + \gamma_{k[i]}+\epsilon_i
$$
Where $j[i]$ and $k[i]$ denotes the group memberships for individual $i$.
In R, I can estimate $\...
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measure Discrimination and Calibration in case-control study
When I adopt a case-control study for risk prediction models of CC, how I can measure Discrimination and Calibration?
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Interaction effects in modeling with multicollinearity
I have a large model in r like:
sales = ai+ x1 + x2 + x3 + x4 +(x1x4) + (x2x4) + (x3*x4), where x4 is a dummy for a certain interventoin. As a result, i wanted to analyse the effect of x1,x2,x3 during ...
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Why the log likelihood is positive in some cases
I have a log likelihood that looks like the following.
$$ \log(p(Z|\Theta)) = -\sum_{p = 1}^{N} \left[ L \log\left(\pi\left(A F(p, \Theta) + \sigma_n^2\right) \right) + \frac{\sum_{l = 1}^{L} Z_l(p) }{...
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Does Arima (1,0,1) exist? Are there any articles station Arima (1,0,1)? How to intrpret Arima (1,0,1) summary results? [duplicate]
I have dataset that corresponds to year (from 1930-2020) and volume of sediment. I have to predict the volume for next 50 years. While trying ARIMA in R I tried different models like (1,0,0), (1,1,0) (...
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carry over effect
When testing the carry-over effect (period*treatment) for cross-validation by GEE, do I actually need to bring in the main factors period, and treatment to the GEE model?
(1) Y = intercept + (...
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what to do if I have two different models for same data?
There's two regression models for same data.
The two are known very precise before but now they are generating conflicting predictions.
In this case how can i handle this?
Should i perform stepwise/...
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