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

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14 views

regression for angular/circular data

I have supervised learning problem where targets are angles. If I would do simple regression then numbers 360 and 1 would be far away for my model, but actually they are close and predicting x and y ...
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6 views

Regression of irregular time series

I am beginning to look at high frequency data sets. I have only ever dealt with regularly spaced data up until now so wondering what best practice is. If I have two time series X and Y with Y being ...
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1answer
23 views

Logistic Regression - Adding interactions makes Independent variable statistically insignificant

My name is Abhi & I am trying to better understand logistic regression by solving a few practice problem. I am using R and RStudio as the development environment Problem Statement Given the age, ...
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9 views

Universal, simple to use method of estimating 1 variable from 3 input variables

Im looking for a method that would allow me to estimate the value of 1 variable, described by 3 other variables. I have a set of measurement data collected with my camera. Each record consists of: ...
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12 views

Is positive coefficient of price correct in a multiple regression model

I am currently undertaking forecasting of energy sales (kWh) for our industrial customers. From historical data gathered from 1993 to 2013, a graph of price per kwh against sales kwh shows a positive ...
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6 views

Regression with Census variables

I seek to model change in school performance over three years (2010 to 2012) using a number of socio-economic variables. The socio-economic data is available from two census periods: 2000 and 2010. I ...
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5 views

Using multinomial logit to rank observations

I'm trying to devise a model to rank a number of links according to their popularity. The links refer to upcoming events and job offers, and ideally I'd like to have a reasonably simple model that, ...
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1answer
20 views

Model specification with Deflators: methodological question on forecast model

I am trying to build a model to predict one year ahead Earnings per share $(t+1)$ based on variables in year $t$. I’ve seen a lot of models in practice that use the following methodology: ...
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1answer
34 views

Ordinal logistic regression with likert scales

I'm currently have a bit of difficulty determining how to analyze this data via logistic regression analysis. ...
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1answer
35 views

Deriving Regression Sum of Squares (SSR)

In a simple linear regression $SSR = \sum(\hat{y} - \bar{y})^2$ $SSXY = \sum(x - \bar{x})(y-\bar{y})$ $SSX = \sum(x - \bar{x})^2$ $SSR$ can be computed by dividing $SSXY^2$ by $SSX$. Namely, $SSR ...
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1answer
32 views

Regression analysis?

I have scored pig carcasses for injuries at 2 points; immediately after slaughter (slaughter stage 1 [SS1]) and again after the carcases have been washed, scalded and dehaired (slaughter stage 2 ...
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1answer
25 views

Using proper scoring rule to determine class membership from logistic regression

I am using logistic regression to predict likelihood of an event occurring. Ultimately, these probabilities are put into a production environment, where we focus as much as possible on hitting our ...
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5 views

Constrain regression to correctly rank-order certain cases

I am working on a logistic regression model that attempts to predict the probability that individuals will do a certain activity, where each individual can be described by a number of categorical ...
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20 views

Multiple and long seasonality for a SARIMA model in R

While working on a big data set made of 10-minutes-points of information - i.e. 144 points per day, 1008 per week and ...
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0answers
11 views

R geom_smooth: what to write as aes [on hold]

I work with R and ggplot but I'm very new with it. I have already drawn point for 4 different data frames. And now I want to draw 4 regression lines for this points sets. Data frames are packed in ...
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9 views

What is the best test to estimate the correlation between binomial/categorical dataset?

I'm trying to analyze if there are correlations between binomial dataset. I have binomial data (presence/absence) of two variable in different periods and I need to know what is the best way to find ...
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21 views

Geographic regression

I'm working on a project to estimate real estate and started with some classique techniques, such as linear regression etc. The obtained results are already going in the good direction, but to get ...
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1answer
20 views

Model Formula with deflator

I'm having difficulties to find the right model formula for my model: $Y_i=a+bX_i$ where Y and X are both deflated by another variable y1/def ~ x1/def + x2/def ...
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29 views

including interactions in a mixed linear model in R (lme)

I'm trying to test for the effect of soil moisture on transpiration rates. I have plot-level data for 18 plots in 6 different stands of trees (3 plots x 6 stands). I want to treat "stand" as a random ...
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1answer
36 views

Non-significant factors after stepwise regression [duplicate]

I have run a stepwise regression on R. However, the summary of the final model includes some factors that are not significant. Why have these factors not been removed? Should I remove these from my ...
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6 views

Assistance with hazard ratios

I want to compare car accident deaths in two groups of people aged 18-24 (lets use this as the reference) and 24-30 after a certain law was changed using a Cox hazard model using SPSS version 22. I ...
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27 views

Interpretation of the coefficient of dummy regression?

I found this for a week, but I still cannot find anything about it. In a regression, Y = a + b * X + controls +e If we add dummy D=1 for group A and 0 for others, it becomes Y = a + b*X + c*D + ...
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1answer
20 views

Which regression analysis should I use for ranked dependent variables and proportional independent variables?

I am analysing the effect of deprivation on breastfeeding and am wondering which type of regression analysis I should use. It is area level data. Deprivation data is available as a score from 0 - ...
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12 views

Evaluating mean-squared error

Hello I am running a Regression Tree experiment. I am new to Regression Trees, and I am using Mean Squared error to test my tree. I am confused because I am getting a large Mean Squared Error but I ...
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2answers
44 views

Two simple questions regarding GLM

I'm currently doing a modelling project. However, I haven't taken a bunch of statistics classes, so I have to teach myself generalized linear models. I'm reading "Generalized Linear Models for ...
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1answer
30 views

Linear regression and ordinal data

I am running a multiple regression looking at whether TV viewing predicts waist circumference (WC). When I ran through the tests with my tutor we placed WC as the dependant and TV as independent, then ...
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7 views

Empirical logit transformation on percentage data

I have already used the logit transform on my outcome variables (which are displayed in percentages). However, this obviously gives me -INF values and since my data includes a lot of zeros in some ...
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20 views

What is the best way to simulate data for a linear regression model?

I am concerned with simulating data for a linear regression model. I need to control the means, variances, and correlations (covariances) between the predictors and the criterion variable. In ...
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12 views

Is it correct to measure R coefficient for LOG LIN models

I have a model where the $y$ is very skewed and I convert it to log and run a log linear model. But, I have doubts about the way to measure the error, because in the original variables the error ...
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1answer
22 views

Low correlation between predictor variables in linear regression

I know that one if one is trying to perform linear regression, multicollinearity can be an issue because it can "lead to unreliable and unstable estimates of regression coefficients." Suppose for a ...
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25 views

Can PCA scores be used as dependent variable?

I am working on a research project where I have several questions from a survey data that measures the same underlying quantity (my dv), possibly each with some measurement error. I was thinking about ...
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7 views

Choice of dependent variable: Differencing or Controlling?

I was running some analysis where I suspect that a treatment $D$, has opposite effects on two variables $Y^A$ and $Y^B$. To show that, I was thinking about two strategies: 1. Differencing Running ...
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45 views

choosing $β_0$ and $β_1$ to minimize the residual sum of squares

I'm reading a book called An Introduction to Statistical Learning: with Applications in R, and I have a question in regards to the material inside. I understand that we can find the residual sum of ...
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1answer
20 views

Analyzing regression results

I have done a regression model where i determine the number of cubes (independent variable) based on the amount of units i started with for each product type (dependent variables, ...
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1answer
23 views

Understanding Regression vs. Means/Median Results

I am having a little difficulty understanding my results - could someone help me understand how to interpret, and if my process is sensible? Here is an example of what I am doing I am trying to ...
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2answers
25 views

Research on debt recovery

My final year project is on debt recovery data for a debt collection firm. Data such as original/current balances,payments made,DOB, number of contacts made,whether or not a debtor has made insuarance ...
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1answer
25 views

Using OLS for Model Selection and Prediction - Heteroscedasticity Issue

I am new to regression and having problem in solving Heteroscedasticity in OLS. Have done lots of homework and test before seeking your advice. Sharing the background and what I have done to solve the ...
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0answers
10 views

How to calculate prediction intervals in major axis regression using R

Need help in calculation of prediction intervals in major axis regression (MA). I'm using 'lmodel2' package for calculation of the MA, but I don't understand how to calculate prediction intervals ...
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24 views

How do I estimate a time series regression using GMM in the way proposed by Acosta-Ormaechea and Morozumi (2013)?

In their paper Acosta-Ormaechea and Morozumi (2013) propose a use of GMM for estimating a regression in which they try to find the impact of reallocating public expenditure from some unproductive to ...
2
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1answer
28 views

Choosing variable transformations in non-linear relationships

I am confused about how to apply a transformation to my predictor/response variables to test curvilinear relationships. I read about log transformations, polynomials, quadratic functions. But I am not ...
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21 views

Iterative Addition of Variables to Model Based on P Value

Suppose I have 64 columns that I have chosen out of 500+ columns based on the fact that they have the highest pairwise correlation (is this a good way?). I take 16 of these columns and run a simple ...
0
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1answer
16 views

Sum of Squares Constraint Regularisation

Suppose I have a function $g_0\in L_2(\mathbb{R})$ such that we observe $(X_i,Y_i)$, $i=1,...,n$ such that $$ \begin{align*} Y_i & = g_0(X_i) + V_i \end{align*} $$ We wish to estimate $g_0$, ...
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1answer
32 views

Estimation of regression with autocorrelated errors

In a book it is written that, In regression work we typically assume that the observational errors are pairwise uncorrelated. But in most time series data , the successive residuals have tendency to ...
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19 views

Is it possible to determine the maximum predictive accuracy for a given data set with a linear regression? e.g. max adjusted R^2

For example say there are N independent variables, and you make a fit with three of them that has a decent Adjusted R2, how do you know when to stop? This is a theoretical question.
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1answer
37 views

Good machine learning algo for partial derivatives?

Does anyone know of good robust algos to estimate partial derivatives of a regression model? I am talking about a general regression model like this: $\mathbb{E}(y|x_1, x_2, ... x_n) = f(x_1, x_2, ...
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1answer
33 views

Graphical comparison of regression models

Will a graph on predicted and measured values plotted for two models separately be helpful in comparing them?
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12 views

R Sales Modeling with Non-Replenishing Inventory

I'm working on modeling sales for tickets for a specific event over time. The issue that I'm having is that the inventory does not replenish, so I can't have my model predicting over what I actually ...
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1answer
50 views

Closed form posteriors for a simple bivariate Bayesian regression

I'm analyzing a simple linear regression $Y_{i}$~$a+b*X_{i}+e_{i}$, with $e$ being normally distributed with known variance and where I have normal priors on $a$ and $b$. I'm trying to piece together ...
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1answer
35 views

How can I (Should I?) use logistic regression/the logit function to predict outcome of a tennis match in a simple simulator?

I am trying to create a tennis simulator. Specifically I am trying to make a 'random' simulator so that I can see how many times streaks of wins or losses occur, and then compare this to historical ...
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1answer
44 views

Spatially auto-regressive two-stage model

I'm working on a project in which I use a 'Generalized Spatial Two-Stage Least Squares' model, mostly known as $y= X \beta + \lambda W y + u$ and $u = \rho M u + \epsilon_n$ where $y$ and $u$ are ...