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
9 views

ANOVA result with insignificant factors

I'm having difficulty interpreting the result I get from ANOVA. Specifically, if some of the factors I put into the model have an insignificant impact (p-value > 0.05) on the output, does it mean I ...
1
vote
1answer
18 views

What is the value of “X” in a regression equation when dealing with a time series?

I am using excel to add a polynomial trend line to a chart. The chart and the formula of the trend line are shown below. I want to add lines indicating different confidence intervals so I need to find ...
4
votes
2answers
59 views

How do residuals relate to the underlying disturbances?

In the least squares method we want to estimate the unknown parameters in the model: $$Y_j = \alpha + \beta x_j + \varepsilon_j \enspace (j=1...n)$$ Once we have done that (for some observed ...
1
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0answers
17 views

Two-Step estimation

I am currently trying to fit a model that has the following properties: (1) data for several years (2) two decisions/equations (probably involved): (a) one that explains an initial choice of product ...
0
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0answers
25 views

Linear regression with log dependent variable

I have the following regression: $log(Y) = \alpha + \beta X + \epsilon$ with $E[\epsilon] = 0$ and $var(\epsilon) = \sigma^2$. There is no assumption on the distribution of the errors $\epsilon$. In ...
1
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0answers
18 views

Y vs X with spatial variation

I am trying to learn a relationship between two variables Y and X, X is the independent variable. The nature of the relationship is quadratic, from some domain experience, but the relationship itself ...
1
vote
1answer
28 views

Improving a regression model based on diagnostics

I have two continuous predictors ($x_1, x_2$) in my data set and a continuous response variable $y$. The data set is by date for 6 quarters. Since I observed a clear pattern of surge during weekday ...
1
vote
1answer
22 views

Investigating interaction

Please I need to check for interaction before building an explanatory model (logistic regression). I have 16 interaction terms in total. Please how what is the best way to go about it. Will I need to ...
2
votes
0answers
16 views

Aggregating forcast to higher spatial level

I am working on a project doing out of sample estimates of wheat yields at the village level in STATA. I am using a short panel 3 years and a sample of ~3000 villages. We are estimating a RE model and ...
0
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0answers
19 views

How to account for data taken at $t=0$ when using $\log(t)$ in the model? [duplicate]

I have a data set with four observations consisting of the variable $Y$ measured at time $t_0=0$ and at times $t_1, t_2$ and $t_3$. I would like to fit the following model: $$\log(y_j) = \alpha + ...
0
votes
0answers
15 views

Mean square error in log-linear model

Let's consider the following log-linear model: $log(Y_i) = \alpha + X_i\beta + \epsilon_i$ for i = 1, ..., N The fitted value is: $\widehat{log(Y)} = \hat{\alpha} + X\hat{\beta}$ Assuming ...
0
votes
0answers
16 views

Testing and reporting interactions in multiple regression

I have a model with two between-participants predictors -- one continuous (a), and one categorical with two levels (b) -- and ...
0
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0answers
9 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 ...
8
votes
2answers
86 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, ...
0
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0answers
35 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 ...
0
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0answers
26 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 + ...
0
votes
0answers
12 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 ...
0
votes
0answers
21 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
votes
0answers
30 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
votes
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
votes
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 ...
0
votes
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
vote
0answers
26 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
14 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
votes
1answer
26 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
votes
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
votes
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
votes
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
votes
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
votes
2answers
153 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
vote
0answers
32 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
votes
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
votes
0answers
19 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
37 views

Conceptual Question on ARMA model representation and likelihood function

I am facing difficulties in understanding the model from the following paper: ...
1
vote
1answer
63 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 ...
1
vote
0answers
15 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
votes
0answers
40 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
votes
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
votes
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
votes
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
votes
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
votes
0answers
23 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
votes
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
vote
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
vote
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
votes
0answers
10 views

Logistic regression using sklearn [closed]

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
27 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 ...