Questions tagged [linear-model]

Refers to any model where a random variable is related to one or more random variables by a function that is linear in a finite number of parameters.

Filter by
Sorted by
Tagged with
0
votes
0answers
3 views

Pairing conditions to run lmer

I have six conditions and would like to create three pairs of conditions, so that when I run lmer it compares conditions 1 & 4, 2 & 3, and 5 & 6. Here's what I have at the moment: ...
0
votes
0answers
15 views

Which model is a better fit?

Suppose I have 2 linear model such that: Linear model 1: ...
1
vote
0answers
12 views

Comparing significance of variables between each other

I would like to determine the significance of my variables in my model and compare them with each other. I have 6 explanatory variables. Here is my summary of the model: ...
3
votes
1answer
46 views

Is there a formal terminology to describe $X^T \beta - X^T\hat{\beta}$?

We know that a linear model is represented as \begin{align} y = X^T \beta + \epsilon \end{align} where $\epsilon$ is some unobserved error and $\beta$ are the population parameter(s). Let us ...
0
votes
2answers
33 views

Confused on ARIMA's linearity assumption

The AR(I)MA model or Auto Regressive Integrated Moving Average model is one of the most popular linear models in time series forecasting. In an AR(I)MA model, the future value of a variable is assumed ...
0
votes
0answers
10 views

Linear Model with gradient Descent: Adaptive learning rate method

I am analyzing a gradient descent implementation of a linear classifier. Before each gradient update, the learning rate is updated as: ...
0
votes
0answers
30 views

How to fit the intercept

I'm practising using R and I'd like to do this task: So I fitted the model: ...
1
vote
0answers
29 views

Is the following a GLM?

We know that the standard linear model is a partial case of the GLM scenario by taking the identity link function, i.e. $$g(μ)=μ=η=x_i^Tβ$$ However, in one of our past papers we are asked to ...
2
votes
1answer
28 views

Linear Discriminant Analysis for newbie (What is the meaning of dataset is linear separable?)

What is the meaning of "LDA dataset is linear separable"? "the classes are non-linearly separated" "the features have nonlinear relationships" As I know in maths for linear equation and non-linear ...
1
vote
1answer
46 views

MAE regression gives biased regression parameters for symmetric error?

Consider a linear model, $$ y_i = \beta_0 + \beta_1x_{1i} + \beta_2x_{2i} + \epsilon_i. $$ From the Gauss-Markov theorem, I know that, under nice conditions, the $\hat{\beta}_{OLS}=(X^TX)^{-1}X^Ty$ ...
0
votes
1answer
32 views

Unbiased estimator and biased error

I'm having some trouble relating unbiased estimators and bias error. By bias error, I mean the bias error we talk about when analyzing "bias-variance tradeoffs." Is this bias error and an unbiased ...
0
votes
1answer
22 views

Question about notation for constant variance

In the context of linear regression where there is an assumption of "constant variance" I have read this: $$\mathbb{V}(\epsilon_i \mid X_i)=\sigma^2$$ But there are two ways I can read this. Either $...
0
votes
0answers
14 views

p-value for the coefficients of the logistic regression classifier

using Matlab, I have created two logistic regression classifiers: one with all the features (3) and one with only the first 2. I would expect to have the estimation of the p-value of the last variable ...
-1
votes
0answers
13 views

Find the maximum likelihood estimate β1,e in R from a linear model [closed]

Given a data set of heights and weights, we have a linear model. Find the maximum likelihood estimate β1,e. I have R in version 3.2.1 and I cannot find a way to use mle. Please help me! I don't even ...
1
vote
0answers
12 views

Simple linear regression over a moving window

I am trying to find an efficient algorithm that gives the capability to calculate the time series slope for each point over a time window. For example, The time serie has 1 Million points, and the ...
1
vote
0answers
7 views

estimator depending on another independent variable

I think I have a very basic question but I find it a little confusing. I have a model and I want to derive a regression equation. For example, $y=\beta x_{1}+ \alpha x_{2} +\epsilon$ The problem is, ...
0
votes
0answers
9 views

How to statistically compare the coefficient of determination (R2) among multiple simple linear models (nonnested) with same scales (IV's)?

I made two simple linear regression models with the same scales (i.e. X variables, sample size and Y variable). The adjusted R2 was used to compare the good of fit between these models. But, how to ...
0
votes
0answers
6 views

When building a multiple linear regression model, is it possible to form models with both linear and non-linear (quadratic) relationships?

Through backward elimination, I have reduced my model from 6 linear factors to 1, accounting for 68% of variance. I have also found that by squaring one of the variables I previously included, that ...
0
votes
1answer
32 views

Finding the best univariate model

I have the response variable as Profit, and several predictor variables. I have made a multivariate linear model to represent this, and have also made univariate models for every individual predictor ...
2
votes
0answers
26 views

How can I detect a line of points underneath lots of noise? [duplicate]

I've got a set of points where 5-20% of the points model almost a perfect linear line (say +- 0.1% of their value), but the ...
1
vote
2answers
16 views

How to handle a relationship for only non-zero values of dependent variables in linear regression

I have a dependent variable in my model which is non-zero only for part of all observations. The example dataset could look like this: ...
0
votes
1answer
20 views

Why is degree of freedom for SSR equal to p - 1 for linear regresion

Why is that $SSR=\sum_{i=1}^{n}\left ( \hat{y}_i-\bar{y} \right )^2$ have p-1 degrees of freedom? Where p is the number of parameters.
1
vote
0answers
13 views

AbsorbingEffectError running PanelOLS regression with Python

My dataframe looks something like that: ...
2
votes
1answer
24 views

Why I am getting different coefficients for R's classification model?

Dataset Consider the following dataset which measures the price of a computer given different configurations Situation After applying the four-way classification model as below, we have the ...
0
votes
1answer
37 views

Why is there such a discrepancy between the sum of squares I computed and R computed?

Dataset The data is a typical dataset encounted in two-way classification model: Situation I applied two-way anova by running R on this dataset to look at the sum of squares ...
1
vote
0answers
53 views

Appropriate linear mixed-effects model for hierarchical data?

We have some hypothetical data for the abundance of a protein that accumulates in cells with age. The goal is to run a linear mixed model to test how much of the variation in the rate at which cells ...
0
votes
0answers
15 views

Significant interaction between covariate and factor in R

I have a dataset of subjects age, test score, and group (each subject belongs to 1 of 3 groups, let's say A, B, and C). Only the 'group' is categorical. The sample size is different between the groups ...
2
votes
0answers
34 views

Why is vectorization called so?

As I understand a vector is anything with a dimension of n x 1. While a matrix is anything with a dimension of n x n. Where n can be any number. So, to my knowledge, when we convert a scalar ...
0
votes
0answers
18 views

Regressing feature data to regression coefficients

Setup: dependent dataset Y independent dataset X independent dataset Z Idea: Frame the data and linear regress each frame : Yf = af * Xf + bf , with f=1..frames For each frame take the regression ...
1
vote
0answers
11 views

why linear regression gives high mean squared error with robust scaler?

I've been trying to use a pipeline that consists of robust scaler and one of the algorithms like xgboost, ridge, lasso, and linear regression, and they all give better results except for linear ...
1
vote
0answers
16 views

Best analysis for finding impact of variables on margin over time

I have two data sets detailing item number, units sold, sales, COGS, and margin one year apart. I want to determine what had the greatest impact on margin from t1 to t2. This is broken down into 3 ...
2
votes
1answer
25 views

What does it means getting p-values equal to 1 and complete separation in logistic regression?

I was really confused if I should ask this here or in Stackoverflow, but I'll give a shot here. I ran a logistic regression using statsmodels library in Python. However, two things went wrong here (...
0
votes
0answers
8 views

Difference in linear model, but not in either main-effects

My experiment is a 3 (auditory, vibe, multimodal) x 2 (simple, metro) design. I am defining a linear regression model, using contrast codes (-1,1) to compare means between conditions. I am also ...
0
votes
0answers
21 views

Can the sum of squares from an ANOVA be used for variance partitioning?

I am playing around with ANOVA and linear models (LMs) and cannot wrap my head around the difference between the the output of the sum of sq from an ANOVA and the difference with variance partitioning ...
0
votes
1answer
20 views

Time Series, linear regression and ARMA

I have time dependent data, I used linear regression for trend and seasonality, for residuals I used an ARMA (p, q). Then I improved my regression by adding the adjusted values of the two models and ...
2
votes
0answers
21 views

What happens with an asymmetric autoencoder?

Suppose I have an antoencoder where the encoder is a nonlinear function eg Neural Net, and the decoder is a linear mapping. Would this type of autoencoder be able to achieve a lower training loss than ...
0
votes
1answer
29 views

How to fit lm model with user-supplied intercept

I'm trying to input the results from my Unobserved Component Model (time_series_df$s_level) into my linear regression model as the intercept. I've found two methods ...
0
votes
2answers
57 views

How to deal with problems like this ? What machine learning algorithms should be used?

I am new to machine learning and this community too. So please pardon me if i make any mistake while putting up this question. I am trying this https://www.kaggle.com/doaaalsenani/usa-cers-dataset ...
0
votes
0answers
8 views

OLS fit interpretation using p-value

I wanted to find the relation between temperature and infected cases. Can I conclude that AvgLow was significant to predict the number of infection cases? I appreciate your suggestions!
1
vote
0answers
5 views

Effect of choosing a linear model with only weights but with an extra X entry that is always set to 1

If we are to choose a linear model with only weights but augment X with an extra entry that is always set to 1, what effect does it have on the assumption and estimation on the resulting linear model....
1
vote
1answer
36 views

how to get predicted intervals? code no giving me those values [closed]

I am doing a cross validation in a training data and I am getting my predicted values with my test data. I want to do a plot with predicted versus observed with the predicted intervals but my code is ...
0
votes
2answers
26 views

write model based on R code

As shown, y is Wear. X is Brand (total 5 brands). Why summary show 4 brands variable? How to write model based on R code? Is model wear=beta0+beta1*brandAjax+beta2*brandChamp+beta3*brandTuffy+beta4*...
0
votes
0answers
15 views

1D representation for 2D toy data (about linear separability)

suppose there is a dataset with 2 features x1, and x2. the points (-1;-1); (1; 1); (-3;-3); (4; 4) belong to class 1 and (-1; 1); (1;-1); (-5; 2); (4;-8) belongs to class 2. I am confused in terms of ...
1
vote
1answer
28 views

Correctly apply linear model for categorical independent variable

This question is about the way to go with a very common statistical model: Continuos dependent and categorical independent variable. In my stats class I learned to use the ANOVA: check assumptions, ...
2
votes
0answers
147 views

How much heteroscedasticity need to be present in order to justify the use of robust standard errors?

Im trying to figure out if my data is heteroscedastic and if I need to use robust standard errors (Huber-White standard errors). The dataset contains 70 000 rows and 5 columns. Y is a numeric ...
1
vote
0answers
27 views

Comparing coefficients in GLM with unknown dispersion parameter

If $\alpha$ and $\beta$ are two coefficients in a GLM with unknown dispersion parameter, is it possible to perform the Hypothesis test $H_{0}: \alpha=\beta$ vs $H_{1}: \alpha \neq \beta$ ? I ...
0
votes
1answer
89 views

linear regression indicator for variables all have different values in R

I have 6 values: id, age(=0 if<24;=1>24) sex(=0 if female;1=male) week blood trt(1,2,3) Question asks write a model for each group with linear trend in week, age, sex, and all their ...
1
vote
0answers
26 views

Comparing coefficients in GLM: a consistency issue

We have a GLM, and we wish to check if coefficients within the model are equal. However, we have come across a small consistency issue and we are not sure how to proceed. For example, let $\alpha$ ...
0
votes
0answers
27 views

Negative binomial modelling versus transformed linear modeling

My dataset (Data) contains data on distance traveled by an organism (Distance) based on their genotype (the two genotypes are A and B). For each genotype, there are 3 replicate genetic lines (A1,A2,A3,...
0
votes
1answer
79 views

Linear probability model with fixed effects?

If I want to estimate a linear probability model with (region) fixed effects, is that the same as just running a fixed effects regression? Maybe I'm getting tripped up with the language and whether I ...

1
2 3 4 5
36