Tagged Questions

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

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0
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0answers
6 views

Support vector regression in weka

I am using SVR for statistical down-scaling of precipitation. I have taken the first 3 factor scores in principal component analysis of variables as predictors and precipitation as predictand. As ...
6
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2answers
53 views

Is there an elegant/insightful way to understand this linear regression identity for multiple $R^2$?

In linear regression I have come across a delightful result that if we fit the model $$E[Y] = \beta_1 X_1 + \beta_2 X_2 + c,$$ then, if we standardize and centre the $Y$, $X_1$ and $X_2$ data, ...
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0answers
31 views

Transform time-dependent data

I have pollution data (quantitative) plotted against time (categorical), the hours of the day. Via ANOVA testing I've found significance at many of the hours, however, the relationship is definitely ...
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0answers
24 views

OLS derivation question [duplicate]

How come I always see the derivation of $\hat{\beta}$ in OLS using matrix differentiation and solving for when the derivative is $0$. Couldn't one just derive it also by noting that in $Y = X\beta + ...
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0answers
11 views

How to calculate y predictor based on ANCOVA estimates? [duplicate]

My formula looks like this: lm(formula=BearWeight ~ honey + age, data=BearData) my output looks like this I am told to interpret each estimate and then use the estimates to predict the weight of a ...
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0answers
18 views

KNN Regression in R - using KKNN package [on hold]

I have been trying to figure out how to plot a multiple regression for a training set with the K(KNN regression). The package name is KKNN for R. The line below expresses the multiple regression model ...
3
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0answers
25 views

Regression using aggregate (averaged) data

I'm doing a project involving the impact that different college grading systems have on MCAT performance. I have access to the following data: Grading system by college Median MCAT score by college ...
0
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1answer
18 views

Correlation of change in expression with response variable

I have paired gene expression data before and after a treatment, as well as an ordinal response variable with 3 levels for each sample after treatment. I am interested in the correlation of the ...
0
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0answers
11 views

handling trend in predictor and response variable

I am trying to create a linear regression model containing two predictors and 1 response variable. My response variable has a short term pattern, i.e. surge during weekdays and slump during weekends ...
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0answers
22 views

regarding skip the intercept term once it is not statistically significant [duplicate]

After building the regression model, the intercept value is not statistically significant Is that reasonable to just skip it in the final regression model?
1
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0answers
25 views

Bootstrapping with bootstrap sample greater than original sample

My original sample has 350 observations drawn randomly from a population of 60,000 people. My independent variable is Default, with 35 observations with value of ...
0
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0answers
11 views

Ideas , if possible to reduce number of predictors before applying shapley value regression

The shapley value regression method (lmg) is very computational intensive for a larger number of variables. Is there/Is it possible to limit the number och screen the variables in some clever way ...
1
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0answers
19 views

Intution on Interchangability of Regression and Classification

Dear Oracles of CrossValidated, I've been trying to gather intuition on the relationship between methods that seems to be escaping me. Can someone explain how regression and classification can be ...
0
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1answer
23 views

Are insignificant variables included in calculation of predicted probabilities?

When calculating the predicted probabilities in a logistic regression model, do we consider all the variables or just the significant ones? For eg: Let's say my model has: dependent variable Y and 3 ...
0
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0answers
31 views

Deriving single linear regression parameters in terms of multiple linear regression parameters

Suppose the true population model is $$\ln(wage) = B_0 + B_1 \cdot education + B_2 \cdot experience + v,$$ where $v$ is the error term. Suppose the model is estimated as $$\ln(wage) = B_3 + B_4 ...
0
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0answers
20 views

Should I do this ARMA model?

These are the autocorrelations: As one can see, it is quite low around 0.02 for the first lag. But it is significantly nonzero, as the blue lines indicate. However, I dont think it makes sense to ...
0
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0answers
11 views

What does the matlab function anova(mdl) do?

My data have one response and several predictors. These predictors are continous, not categorical. After regression, I wish to decompose the total ss on each predictor. With regard to this, I have ...
0
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0answers
14 views

creating an indexed dummy variable as a predictor in OLS

I am performing on OLS with two predictors and a response variable. The data is a time series of 450 days approximately. There is an irregular pattern in my response variable - it sometimes ...
2
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2answers
152 views

How to prove linearity assumption in regression analysis for a continuous dependent and nominal independent variable?

I want to check the assumptions for applying linear regression analysis. So, among others I check the linear dependency between my dependent (which is continuous) and my independent (nominal or dummy) ...
1
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0answers
29 views

Deriving the maximum likelihood for the parameters in linear regression

Notation: $\textbf{w}$ is an M-dimensional vector of parameters (including the bias parameter), $\textbf{x}_n$ is an M-dimensional vector of the features of each training example, $\textbf{t}$ is an ...
0
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1answer
25 views

Back-transforming elasticities to level coefficients, with standard errors

I would like to use some literature estimates of supply and demand price elasticities in an illustrative model that is in levels, not logs. The elasticities come from models of the kind $$ \ln ...
0
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0answers
18 views

regarding using Lasso and Random forest based on the variable selection result coming from other processes

After the process of data exploration process and discussion with client, we set up a set of variables as follows: T1, T2, T3, T6, T8, T2*T3, T1*t6 During ...
0
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0answers
36 views

Conceptual Question on ARMA model representation and likelihood function

I am facing difficulties in understanding the model from the following paper: ...
1
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1answer
62 views

Logistic Regression Assumptions

I am preparing a presentation on logistic regression. I applied logit model to a data set and now want to check whether my model meets logistic regression assumptions. I don't exactly know how to do ...
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0answers
13 views

Why all coeficents of features of model are zero while I have high deviance using glmnet?

I'm using gmlnet to learn lasso regression model. model<-cv.glmnet(x, y, alpha=1, nfolds=10,parallel= TRUE) when I learn model and look at the model it's like this : ...
2
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0answers
39 views

Regression with non-zero mean errors

I want to fit a linear regression model of the type $$y_j= x^{\top}_j\beta +\epsilon_j,\,\,\, j=1,\dots,n,$$ However, the distribution I am using for modelling $\epsilon_j$ does not have mean zero, ...
0
votes
1answer
27 views

An algorithm to predict one of two values based on a linear model

I would like to run by you an algorithm for predicting one of two values from a testing data set, based on a linear model applied to a training set. Please let me know whether this algorithm makes ...
0
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0answers
17 views

Interaction with contrast and dummy coding

I have a question regarding the interpretation of an interaction using categorical variables where one is dummy coded (0, 1) and the other is contrast coded. The variables are: Var1: 3 levels, ...
0
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0answers
32 views

Kernel Estimator [on hold]

What is the behavior of the kernel estimator when a single observation moves to a very large value, that is $(X_i,Y_i)\to (X_i,Y_i\pm c)$ with $c\to \infty$ for a fixed $i$. and as one of the ...
0
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0answers
26 views

The Analytics Edge - NBA Basketball Problem [on hold]

I am studying The Analytics Edge and have some questions regarding the method used. https://courses.edx.org/c4x/MITx/15.071x/asset/Week2_Recitation.R ...
0
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0answers
9 views

How to modify regression diagnostics for weighted least-squares?

I am fitting a weighted least-squares model: $Y = \beta \ X + \frac{\epsilon} {\sqrt{w}}$ ( $ Y$ is an average of $w $ observations; ). For reference: I am using R, with code that reads something ...
4
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0answers
19 views

Rank deficient bootstrap resamples

Despite years of stat courses I'm afraid I may still not completely understand bootstrapping. My question here relates to nonparametric boostrapping of regression models. As i understand it you draw ...
0
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0answers
12 views

Yule-Walker in SAS

My professor claims that I can implement a Yule-Walker transformation by simply typing in y = x / nlag = 1 method = yw; This always crashes when I run this code. If anybody has a simple one line ...
1
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0answers
9 views

Fixed effects in panel data, correlations/coefficients don't add up

I am doing a regression on panel data for firms. The dependent variable is the Marginal revenue product of labour (RPL), i.e. labour productivity, and the independent variable is the average wage of ...
1
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1answer
26 views

Hypothesis test for the response variable in a least squares regression model

I have an equation where time it takes to get to work is based on time it takes to depart, number of red lights hit, and number of trains you encounter. The model is shown below: ...
0
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0answers
10 views

Logistic regression using sklearn [on hold]

I am using sklearn to implement logistic regression. this is code I have written till now ...
0
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0answers
15 views

Methods for predictive modeling on continous target

I am trying to put a continuous target into predictive modelling method. The target is an amount that can range from 0 to unknown. I have roughly 1000 records (for modelling and validation ...
0
votes
1answer
26 views

regarding the explanation of interaction plot

I was trying to draw an interaction plot for two predictor variables as follows: interaction.plot(xtest[,2],xtest[,8],y) I got the following plot. I do not know ...
1
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1answer
20 views

Linear Regression Point Estimates

Suppose we construct the linear relation (using least squares) $$\text{Weight} = \text{Height}\cdot b + c$$ As I recall from school 30 years ago, Weight is normally distributed with the mean of ...
0
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0answers
16 views

input variables with different order of magnitude

I need to build a prediction model based on a data set with 5 different independent variables. The data set looks like as follows. The variables in col4 and ...
0
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0answers
14 views

Regressions and statistical significance [duplicate]

Why does the statistical significance of the variables in a multiple regression lower compared to individual simple regressions?
0
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0answers
10 views

Is the approach for PLSDA for categorical variables the same as that used for “PLS for regression”?

I understand the approach used for partial least squares for regression (PLS) where the principal components are chosen such that the correlation between the scores in the principal component space ...
0
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1answer
35 views

Polynomial regression P value is getting altered

I am running following data and code for analyzing non-linear regression and to get simplest equation of curve that fits the data: ...
1
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1answer
40 views
2
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1answer
42 views

linear regression

I am reading a paper and come across the following information: ...
0
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0answers
27 views

does multiple regression sound right?

we provided a hot/cold description to students of a Male/Female substitute professor and asked them to rate them on a likert scale (1-7). With this data, I would like to see if there is a relationship ...
0
votes
0answers
20 views

the reason that adding one more predictor variables will cause lm model to be all NA

I have a data set with multiple predictor variable candidates, and try to experiment with different combinations. During the experiment process, I tried using the first 9 variables, ...
1
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1answer
21 views

Interpretation of significant interaction

I look for an intuitive understanding of interaction effect in ANOVA or regression. Let's keep things simple as the following. Suppose we have a standard 2 x 2 factorial design, where each factor ...
0
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0answers
15 views

Distribution of Standard Deviation of 2 Variable Linear Regression

Assuming we have a fit: $\hat Y= \alpha + \beta (X-\bar X)$ Such that: $Y_i=\alpha+\beta(X_i-\bar X)+\varepsilon$ The standard deviation of $\varepsilon$ is $\sigma$. Estimated in an unbiased way ...
0
votes
1answer
28 views

Multilinear Model with fixed intercept

I would like to fit the following model Y (t) = m (t) + b * t + g * C (t) + N (t) with m (t) to be the long term mean monthly values (remove seasonal component), b ...