2
votes
1answer
22 views

When to use zero-inflated poisson regression and negative binomial distribution

I have a fairly simple dataset looking at the relationship between the first nesting date of a bird in a given year (Date) and the birds overall fledgling production from that year (Fledge; count data ...
0
votes
0answers
33 views

R: Prediction using glm() [migrated]

I am using glm() function in R with link= log to fit my model. I read on various websites that fitted() returns the value which we can compare with the original data as compared to the predict(). I ...
1
vote
1answer
60 views

linear regression intercept does not match

I have done a linear regression in R, using glm function. The calculated intercept says 0.98, but when I plot it, it does not seem to hit the estimated intercept on Y axis. Its far below. Here are my ...
9
votes
1answer
118 views

Increased Type I error - GLM

Some of you might have read this nice paper: O’Hara RB, Kotze DJ (2010) Do not log-transform count data. Methods in Ecology and Evolution 1:118–122. klick. In my field of research (ecotoxicology) ...
0
votes
0answers
15 views

Zero inflated model problem: system is computationally singular

I'm using R.After getting an error asking me to provide starting values for a glm (poisson family), I took a look at my data and realized I had quite a bit of zeroes. So, I tried zeroinfl from pscl. I ...
0
votes
0answers
13 views

package in R for BMA of a logistic model?

I am trying to perform analysis similar to Gerlach et al. (2002). it involves predicting the posterior probability of a particular binary outcome using the previous 5 observations. I was just ...
0
votes
0answers
11 views

rebuild model based on what columns a record has

I've built a model in R using glm, and in the new dataset that I need to predict, there exist some new levels for the columns that are non-numeric. I know there are so many approaches to deal with ...
2
votes
0answers
33 views

What GLM family and link function for “proportion of time”?

A simple question to which I don't seem to find the answer anywhere. I have a response variable duration of time spent doing A of individuals tested for ...
1
vote
1answer
32 views

Interpret GLM Output (Gaussian - identity) with B0 close to zero

I am doing a GLM (guassian - identity) using R. I am modeling different variables (8) to try to understand what creates brand value in an organization. Some extracts from the output are: ...
0
votes
1answer
50 views

Binary logistic regression with interaction terms

I have been reading several CV posts on binary logistic regression but I am still confused for my current situation. I am attempting to fit a binary logistic regression to a series of continuous and ...
1
vote
1answer
88 views

Count data on proportion or different kind of type?

I really do not know which kind of variable my response data is. I cannot find any answer to my question in the world wide web. I have the results from a survey of 900 farmers. Each farmer told how ...
0
votes
0answers
23 views

Using glm(family = guassian) on data that is actually Poisson. Strange non-symmetrical bias

Let's say I want test the consequences of assuming a normally distributed response variable in a glm model when it is really Poisson. I simulate some data with some quadratic terms. ...
0
votes
0answers
28 views

linear or poisson regression for monsoon onset

I was interested to know if I have historical data of onset of monsoon every year (where onset for each year is in Julian day) and I want to do a regression of onset against time to study whether the ...
4
votes
0answers
56 views

How exactly is the sum (or mean) centering constraint for splines (also w.r.t. gam from mgcv) done?

The data-generating-process is: $y = \text{sin}\Big(x+I(d=0)\Big) + \text{sin}\Big(x+4*I(d=1)\Big) + I(d=0)z^2 + 3I(d=1)z^2 + \mathbb{N}\left(0,1\right)$ Let $x,z$ be a sequence from $-4$ to $4$ of ...
1
vote
0answers
27 views

combining and contrasting time course GLMs using R

I am analyzing some time course data in which I have set up a GLM using R for each subject. Each GLM I want to run is an attempt to extract estimates of different behavioral conditions effects on the ...
0
votes
1answer
39 views

GLM with categorical predictor on R

I need to do a model with a generalized linear model. My data are these: habitat : 0 or 1, group : 1 or 0 , mortality : yes or no, and the numbers of individuals for each case (habitat, group and ...
0
votes
0answers
70 views

R² (squared) from a generalized linear mixed-effects models (GLMM) using a negative binomial distribution

I try to compute the marginal and conditional R² for a GLMM using a negative binomial distribution by following the procedure recommended by Nakagawa & Schielzeth (2013) . Unfortunately, the ...
1
vote
0answers
60 views

Logistic regression with multi-class features in R

I'm working with a data set like the following: X = ...
2
votes
0answers
31 views

R GLM verifying performance statistics for validation

I do not want to say my AUC is 0.77 and find out I am overlooking a lot. Below is my code and a two question at the bottom: ...
1
vote
0answers
45 views

How does the cubic spline basis exactly look like

By the definition (1) $S(x)=\begin{cases} S_0 = a_0x^3 + b_0x^2 + c_0x + d_0, & \text{if }t_0\le x\le t_1\\ .....\\ S_{k} = a_kx^3 + b_kx^2 + c_kx + d_k, & \text{if }t_{k-1}\le x\le ...
0
votes
1answer
46 views

What is the z-value of glm model parameters?

I know what the z-value of a single observation is, that is explained in Wikipedia. But what is the z-value of a parameter in a glm model?
1
vote
0answers
29 views

error structure in Generalized linear models when y is continuous data and errors not normally distributed

Lets say I have continuous y and x variable and I run a linear regression: mdl1<-lm(y ~ x) A generalised linear model should also give me the same parameters ...
1
vote
0answers
37 views

fitting an exponential decay onto a regression line

I have data for adherence to medicines which follows a downward linear trend for about 6 months (from 100%) and then plateaus at about 50%. Another way of describing it is by saying that adherence ...
0
votes
0answers
46 views

Tukey for GLM can't find data in model

I fit a GLM to a dataset. Now I want to see where the difference between my groups is, so I tried to run a Tukey HSD as a post-hoc test. Because of it is a GLM, I can't use ...
0
votes
0answers
20 views

Fisher Scoring v/s Coordinate Descent for MLE in R

R base function glm() uses Fishers Scoring for MLE, while the glmnet uses the coordinate descent method to solve the same equation ? Coordinate descent is more time efficient than Fisher Scoring as ...
0
votes
0answers
45 views

GLM with multiple categorical variables in R : how to interpret the result?

I have a binomial variable that I regress against different categorical variables which I have contrasted to build a reference of an individual Female, Married, aged 35-45, High education : ...
-2
votes
1answer
90 views

Predict y value from glm for a x vector larger than data used in the model [closed]

I have fitted a Poisson regression model using, model <- glm(y ~ x, family = "poisson", data = df) where length of df is 50 ...
1
vote
0answers
65 views

Left skewed distribution implementation generalized linear model

I am very new to modelling and I have a question. I am using a generalized linear model (glm) for my data in R. My response variable is however skewed to the left ...
1
vote
1answer
49 views

Why does a binomial glm give negative predictions?

I'm using count data in quite a simple way, but I cannot understand how a binomial glm can return negative predictions example code, where count of successes increases with responce variable: ...
3
votes
0answers
88 views

Generalized linear model with lasso regularization for continuous non-negative response

I have a big data problem with a large number of predictors and a non-negative response (time until inspection). For a full model I would use a glm with Gamma distributed response (link="log"). ...
1
vote
0answers
65 views

Creating observed/expected ratio using logistic regression

I am using logistic regression to benchmark the performance of some students in different years. I created a scenario as below: ...
1
vote
0answers
51 views

Difference categorical variables R [closed]

I can't figure out how to do the following: I need the following linear predictor $\eta=team_i-team_j$ where, both $team_i$ and $team_j$ are categorical variables, which have 163 categories. Normally ...
5
votes
0answers
63 views

Why are confidence intervals for predicted values so large?

The data for this question can be downloaded with this code: ...
0
votes
0answers
27 views

Logistic Regression Performance on training data set V/s AIC

I am fitting a logistic Regression on data set having 700 variables (after Chisquare test) and 15000 rows. For that I did best subset analysis using glmulti package in R on first 70 variables and got ...
5
votes
5answers
587 views

Logistic Regression on Big Data

I have a data set of around 5000 features. For that data I first used Chi Square test for feature selection; after that, I got around 1500 variables which showed significance relationship with the ...
1
vote
1answer
65 views

Logistic regression: can weights be used as a predictor variable?

I counted the number of birds in a flock, which gave counts like these: ...
1
vote
2answers
151 views

Should the final R glm include only significant levels of factors

I am running a glm in R on data with quite many predictors (~50), both initially continuous and factors. The response is binary and the volume of the data is OK (~100K rows), in order to model ...
1
vote
0answers
143 views

ANOVA on percentages

Please read edit 3 first I am trying to find out the significant factors in a dataset of percentages, a sample of which are below. The difficulty is that the data violates the assumptions of ANOVA, ...
0
votes
0answers
31 views

Parameter covariance matrix for a multivariate (matrix-Y) logit model

I've got a partially-observed unidirectional network. Nodes can be linked (0/1) in one of many ways. For now, lets call them $y_1$ and $y_2$. The unit of analysis is the potential network link ...
0
votes
0answers
54 views

Multi level mixed-effects model in glmer

I have data for a set of users (UID), over numerous dates (date), and over numerous sessions (these are just small chunks of time that a user was active) within each date. For each session I have a ...
1
vote
0answers
34 views

unique spline for different groups in a linear model (and no spline at all for one group)

I have a problem that has puzzled me for a long time. It involves linear models and spline functions. I need to model "time since diagnosis" when some individuals never had a diagnosis. I use Poisson ...
6
votes
2answers
169 views

Parameter estimation with generalized linear models

By default when we use a glm function in R, it uses the iteratively reweighted least squares (IWLS) method to find the maximum likelihood estimation the parameters. ...
3
votes
0answers
39 views

Type I error in Negative Binomial GLM

In the following R code, the expected type I error should be 0.05 (I think), but it is consistently greater than 0.05. I want to know why. ...
0
votes
0answers
81 views

Same p-value when comparing two GLM

This is my first question, please should I write something wrong correct me. I have a question when comparing two GLMs after applying stepwise selection. What I've always heard is that stepwise ...
3
votes
1answer
174 views

Feasible Generalized Least Square in R

I am studying the factors influencing the annual salary for employees at a undisclosed bank. The regression model that I have decided to employ is as follows: \begin{equation} ...
1
vote
0answers
38 views

Maximization of Log-likelihood Numerically and Local Maximum Problem

I am maximizing the log-likelihood function for a generalized linear model without using per-written functions like glm due to the form of the model I have. So to ...
1
vote
2answers
173 views

Fit distributions with glm

I'm trying to fit different statistical distributions (Gamma, Poisson, normal, inverse Gaussian) to my data with a glm. An example could be like this: ...
0
votes
0answers
67 views

R: Weights in glm-function

I'm analyzing a vote result in my country and I'm using a logistic model for this task (glm). The population was asked to vote yes or no, which resulted in an approval-value from 0% to 100% for each ...
0
votes
1answer
84 views

Residuals from glm model with log link function

In the following example: ...
1
vote
0answers
72 views

oversampling glm in R: how to define `weights`

Let's say I have 10 positives out of 1000 observations. I'd like to run glm on the 10 positives and a sample of 10 non-positives (so a total of 20 records in the ...