Stack Exchange Network

Stack Exchange network consists of 174 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers.

Visit Stack Exchange
Make your voice heard. Take the 2019 Developer Survey now

Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

0
votes
0answers
3 views

Modelling percentage and proportion data with GLM's

I would like a simple answer, if there is one, to a question I cannot seem to find on here. What is the best way to model percentages? Say I have a glass that is empty and I fill it with liquid ...
1
vote
0answers
4 views

Orthogonal polynomials with respect to weighted inner product

Recently I have posted a question on SO, but maybe here is better place to ask. So, I have data and I want to fit polynomial of order $k$ orthogonal with respect to weighted inner product of functions:...
0
votes
0answers
18 views

When is it ok to remove observations from a dataset

I have a dataset, equal to 135,997 rows and 9 columns, the head of the table looks like this ...
0
votes
1answer
14 views

Linear regression feature selection equivalent for a classification problem?

I have the following: Label (y): a boolean flag indicating something is good or bad Features (X): lower-level features that are believed to be correlated with the boolean flag. Some of them are ...
0
votes
0answers
8 views

Convert regression parameter standard error estimates to standard deviation estimates

Lets say I fit a linear model (in R), of y ~ x: x <- runif(100,0,5) y <- x*0.5 + rnorm(length(x)) summary(lm(y~x)) The summary output returned is: ...
0
votes
0answers
4 views

Analyzing/modelling discrete numerical responses and determining associations based on categorical co-variates

I need and would be grateful for some advice regarding the analysis of some data that has been gathered and coded by a third party. The data is part of a project regarding performance in the health ...
0
votes
1answer
12 views

Normalized regression coefficients - interpratation

I have data containing several variables. I ran a regression model. Prior to running the model I have normalized the dependent variable Y and the independent variables X1 and X2. After receiving the ...
0
votes
0answers
11 views

Reverse causality: Comparing two studies

I am writing a student-level essay (politics) and have encountered two interesting studies examining a similar variable: once as dependent and once as independet variable. However: (1) The first ...
5
votes
1answer
149 views

Using PCA to reduce dimensionality of training and testing data

I've read so many contradicting opinions that I feel like I need to ask the question myself. Say I use PCA on a dataset with 60 variables and find that I can explain 98% of variance with 6 principal ...
0
votes
1answer
20 views

customized loss function

I am trying to solve a regression problem where I have to predict for how long a machine will be out of order given its status when it breaks. The goal is to fix first machines that are predicted to ...
1
vote
2answers
19 views

Which method to choose when comparing non-nested models

I have 2 non-nested models which I would like to compare. Both models are based on the same dataset but use different predictors. Model1 predictor A+B Model2 predictor B+C I know there are multiple ...
0
votes
0answers
9 views

Coefficient of a model [on hold]

What does mean coefficient of a model negative? I am doing research on employee satisfaction with the performance appraisal system. I get a negative coefficient (constant) does it mean that if there ...
2
votes
1answer
21 views

Confidence interval of a log-linear regression

AIM: Make a confidence interval statement on a log-linear regression I have read posts like: Interpreting Standard Deviation of Natural Log Transformed Data Lognormal Regression? But they do not ...
0
votes
0answers
20 views

GDA vs Logistic Regression

Given an arbitrary dataset, how would one decide whether to use GDA or Logistic Regression? Is the only way to choose via trying both and selecting the one with better performance or is there some way ...
2
votes
0answers
13 views

How to interpret a two-way interaction in a 3-way interaction model

I am trying to predict y with variables a, b and c. I have two models and I get different results depending on how I fit my model. Model A is the simpler model, in which I exclude variable c. In ...
1
vote
2answers
64 views

In Bishop's textbook, is the example of overfitting exaggerated?

Here, the data $x$ are randomly generated, and $t$ are generated by running $x$ through a function $\sin(2\pi x)$, then Gaussian noise is added. Bishop's text then tries to fit those data using a ...
1
vote
0answers
19 views

Confidence interval to use when residuals non normal?

I have done regression but residuals not normal...When I take out outlier residual are normal.but the outlier is important data so I leave it in...In order to use my regression result do I reduce my p ...
0
votes
0answers
29 views

Parameters in the prior and posterior distributions

In the answer of this question Joint posterior distribution of $(\mu,\sigma^2)$ in the Normal model (the expression below $(1)$ ), Why the parameters are $\frac{1}{2}(v_o+n+1,v_os_o^2+(n-1)s^2+n(\...
0
votes
1answer
10 views

Differences between Wald Statistics and P-values obtained with Dummy Coding vs. Direct Coding in Cox Models

Using the larynx dataset (source: Survival Analysis Techniques for Censored and Truncated Data) to illustrate, supposing you want to estimates the hazard rates of event for stages 2 and stages 3 ...
6
votes
2answers
207 views

Does it make sense to use the slope of trend line from a regression as a ratio between x and y

The regression plots Hours (y) vs jobs (x). Let's say the equation is: y = 0.4x + 90 Is it okay to say that the time for each job is 0.4 hours?
2
votes
0answers
40 views

Models and standard scores

I'd like to use standard scores to describe a variable $y$. If I always measured $y$ in a particular place and time, I'd just take the mean and standard deviation of $y$ and then calculate the ...
1
vote
0answers
7 views

How to compute/plot the contribution of each original descriptor in a final PLA regression model?

New to scikit-learn. I am using v 20.2. I am developing PLS regression models.I would like to know how important each of the original predictors/descriptors are in predicting the response. The ...
0
votes
2answers
32 views

Insignificant Dummy Variable in Regression

How can you refer to insignificant binary dummy variables in the results chapter of papers? E.g. when it has been found that gender is not significant. Can you state that there are no significant ...
0
votes
0answers
4 views

Testing if the strength a correlation is moderated by a continuous variable

Participants rated different behaviors on how risky they think the behavior is, and then rated how likely they are to engage in the behavior. I want to know if their ratings of the behavior's ...
3
votes
2answers
91 views

Exclude observations with measurements below limit of detection?

I am analysing a dataset for the relationship between an exposure variable x and a response y (in my case, these are urinary ...
0
votes
0answers
31 views

How to determine the right answers from different sources [on hold]

Situation: There are n number of questions Q1..Qn Each question has one and only one correct answer (unknown to me, and when the answer is B, Z is as wrong as C is) I have some answers to those ...
0
votes
0answers
15 views

flight delay prediction [on hold]

Suppose that there is an airport and we have the average of flight delays for every day of the first month of 2018. Lets say the first day had an average flight delay of 2000 seconds and the second ...
0
votes
0answers
15 views

INTERPRET A REGRESSION MODEL WHEN OUTCOME VARIABLE IS LOG TRANSFORMED [duplicate]

I have used a linear model between a log-transformed outcome variable and a group of predictor variables. In this model, the dependent variable is in its log-transformed state, and the independent ...
1
vote
0answers
26 views

Is there any two-stage procedure for elastic net as LASSO?

I read this post Why use Lasso estimates over OLS estimates on the Lasso-identified subset of variables? . It says the LASSO shrinkage causes the estimates of the non-zero coefficients to be biased ...
0
votes
0answers
12 views

Combining many sets of data with different intervals

I have a dataset to analyse which goes somewhat beyond my stats knowledge. Rather than explain the actual data I've reworded into something equivalent (it's not actually about crime). What I have: ...
2
votes
0answers
21 views

Constraints across related dependent variables

I'm working on model that uses a set of features like track_type, driver_age and some lag variables to predict the number of <...
0
votes
0answers
9 views

Should General Linear Regression be used to analyze sales data with multiple products?

Consider the following simplistic example: a retailer sells 3 interchangeable products and wants to understand how a discount on one product influences sales of other products. A data sample for 3 ...
0
votes
0answers
14 views

Should I use statistical inference on this “sample”?

The dataset gets its data from thousands of individuals throughout the US who update the same spreadsheet of about 5000 rows. This dataset contains address for individuals and is updated by the ...
14
votes
5answers
1k views

How do I compute whether my linear regression has a statistically significant difference from a known theoretical line?

I have some data which is fit along a roughly linear line: When I do a linear regression of these values, I get a linear equation: $$y = 0.997x-0.0136$$ In an ideal world, the equation should be $y ...
0
votes
2answers
34 views

What is represented by the y-axis in a loess smoothing curve?

I'm working on the Titanic data and I plotted local regression curves for a couple predictors. ...
0
votes
1answer
27 views

KNN regression: Why does my In sample RMSE look like my out of sample RMSE across K values?

I'm expecting the RMSE plot for my KNN regression model to look like the above image but I'm getting the below when running my code hosted here. Any ideas on what could cause this? I believe something ...
0
votes
0answers
17 views

How to code a categorical variable for logistic regression with overlap in the categories/subgroups?

Suppose I have a categorical variable consisting of four levels: a, b, c, and d. When these levels are mutual exclusive, I would use dummy coding - so three dummies with for example level a as ...
0
votes
0answers
31 views

How to correct standard errors for heterogeneity and intra-group correlation?

I got my article manuscript back from review and one notion from a reviewer was that in my analyses "[s]tandard errors are not corrected for heterogeneity or intra-group correlation", s/he apparently ...
1
vote
0answers
10 views

How to interpret economic significance with the left side is natural log variable and right side is decile ranking variable

Hi I have searched for many articles but still confused about the interpretation of the economic significance. Here is the result: ln(fees)=10.15+0.18 size (decile rank variable)+ other variables. ...
0
votes
1answer
22 views

Kernelize Linear Regression

We can kernelize Ridge regression as shown in these notes: https://www.ics.uci.edu/~welling/classnotes/papers_class/Kernel-Ridge.pdf. However would it be possible to find a vector $\boldsymbol\alpha$...
0
votes
1answer
22 views

How to approach a classification problem when the sample size is only about 50

I was given a data consists of 53 people and I was asked to come up with a general classification rule based on biomarkers that can be used to classify each person under one of the three possible ...
0
votes
1answer
19 views

How does a Logistic regression model converge if most variables are not linear with the log odds of the dependent variable?

I have a dataset (unfortunately cannot disclose any part of it) which has a binary response variable. For each independent variable, I calculate the log odds of the positive cases given each value of ...
0
votes
0answers
11 views

Using waldtest with matrices [on hold]

I have a lot of data so my variables are organized as matrices. I am trying to do the following code and test for H0: b2=b3=0 ...
7
votes
1answer
204 views

Linear regression minimising MAD in sklearn

The standard sklearn linear regression class finds an approximated linear relationship between variate and covariates that minimises the mean squared error (MSE). Specifically, let $N$ be the number ...
0
votes
3answers
52 views

How can I understand the concept of a noise in machine learning?

In Bishop's book, one of the first examples is shown here Essentially, the data $x$ are randomly generated, and $t$ are generated by running $x$ through a function $\sin(2\pi x)$, then Gaussian ...
1
vote
1answer
74 views

Algorithm for forward stepwise regression

I am trying to implement the algorithm for forward stepwise selection following the book "Introduction to Statistical learning": The steps listed in the book are: ...
0
votes
0answers
25 views

How do I check my logistic regression for linearity?

My understanding is that logistic regression assumes a linear relationship between the logit of the outcome and each predictor variable. I'm working on a case study from this MIT course. My model is ...
0
votes
0answers
16 views

Logistic regression on aggregated counts [duplicate]

Normally when we do logistic regression, we would have a dataset something like: X1 X2 Y 1: A 3 0 2: A 4 0 3: A 3 0 4: B 4 1 (4 observations) However,...
0
votes
0answers
35 views

How can RMSE be compared between a regression model and a neural network model?

In the calculation of RMSE, linear regression uses degrees of freedom(n-p) as divisor and neural network(feed-forward in my case) uses the total data number(does it have degrees of freedom as well?). ...
0
votes
0answers
15 views

Linear Regression in my time series class [on hold]

I need help on creating sas code for a linear regression for electric consumption versus time in years from april 1997 to april 2018. A sample of my data is shown below in the images. I am using SAS. ...