# Questions tagged [intercept]

The intercept in regression-type models is the value of the Y variable when all X variables are 0.

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### Permutation test on the intercept in MANLY(1997) framework?

We assume to have the following regression model: $Y=β_0+β_1X_1+β_2X_2+ϵ$ I recall here the Manly procedure (from another post here :How to do permutation test on model coefficients when including an ...
1answer
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### suppress intercept in regression when having more than one categorical variable coded in dummy variables

friends: according to the following link https://stats.stackexchange.com/a/11068/196391 and what I saw in some papers, we can supress the intercept and consider ALL the dummy variables (which have ...
1answer
645 views

### I computed ARMA equation from R manually but never got the same result with predict() or forecast() provided by R

I've got a little problem here. I've been doing analysis with time series data using ARMA, and it always turns out that the parameters I get from R didn't fit to my computation when I do it manually. ...
0answers
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### How to fit a model that forces all points through zero while allowing for interaction effects

I'm trying to build a model to predict the percentage of a target audience reached as a function of the amount spent on several media channels (e.g. TV and radio) and the type of campaign. The fitted ...
1answer
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### Why is softmax regression often written without the bias term?

I am familiar with softmax regression being written by: $$P(Y=y\mid X=x)=\frac{e^{[Wx+b]_{y}}}{\sum_{\forall i}e^{[Wx+b]_{i}}}$$ for the change of the class of $Y$ being $y$, given observations of $X$...
2answers
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### What is the reason for not including an intercept term in AR and ARMA models?

In econometric literature it is usually argued that in case of estimating an equation, an intercept term must be always included regardless of its statistical importance because removing the constant ...
1answer
935 views

### Which intercept R selects (binomial glm)?

I have a problem with an analysis. I'm doing a binomial glm with two categorical factors that are loc and trat. I do not understand how R deals with the intercept (what statistical explanation does ...
1answer
2k views

### Interpreting significance of the intercept in a regression analysis

For my thesis, I'm conducting several linear regression models. In total I have 15 dependent variables, so in my appendix I have 15 regression tables including 4 models. Example: I'm trying to ...
1answer
57 views

### Include intercept/error term in logistic regression model specification

Short question, When specifying a logistic regression model as below, does one also include B0? In other words, does the bottom part of the equation look like: A. 1 + exp(-(B1X1 + B2X2) B. 1 + exp(...
2answers
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### Logistic regression intercept representing baseline probability

In a linear regression, when you standardize your numeric variables, the resulting intercept has the same value as the mean of your sample. Is there any way in a logistic regression, with numeric ...
2answers
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### What does the formula y ~ x + 0 in R actually calculate?

What is the statistical difference between doing a linear regression in R with the formula set to y ~ x + 0 instead of ...
0answers
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### Is it necessary to include all levels as random intercepts in a multilevel model when they are perfectly nested?

I am running a mixed-effects model in R and I want to have random intercepts for two sampling levels, country and site. The ...
1answer
133 views

### Standard Error of the Intercept in ARIMAX model

I'm trying to estimate the standard error of the intercept in ARIMAX(1,0,2) model using R. Since the reported 'intercept' in regression output is actually some kind of mean value I applied this ...
1answer
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### How to change a weight/bias with gradient

After watching 3Blue1Brown's tutorial series, and an array of others, I'm attempting to make my own neural network from scratch. So far, I'm able to calculate the gradient for each of the weights and ...
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### Why are bias nodes used in neural networks?

Why are bias nodes used in neural networks? How many you should use? In which layers you should use them: all hidden layers and the output layer?
1answer
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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(...
0answers
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### Calculate output nodes (consumer acceptance) of neutal network

To make it a bit easier I am using round numbers (integers) in this example. We have to calculate the value for consumer acceptance. Therefore we have the following input variables (fat = 3; salt = 2)...
4answers
950 views

### Does the intercept in a logistic regression capture the unobserved effects?

Theoretically, does the intercept term in a logistic regression model capture all unobserved effects? In other words, in a logistic regression model with a perfect fit (i.e. all relevant variables ...