The tag has no usage guidance.

learn more… | top users | synonyms

0
votes
0answers
11 views

Residual Not Normal for Model Seasonal Time Series in R

I got a problem when choose the model for forecasting with time series. I'm in a middle writing my Thesis. My data have a seasonal pattern so, i tried use this model ...
1
vote
1answer
28 views

Positive serial correlation

Blows are the pictures from my course lecture. The lecture states only the second picture shows a positive serial correlation, and the first picture requires time to be added as a predictor while ...
0
votes
2answers
33 views

Regression Analysis — Correlation of Residuals

I see a lot of info on how to detect correlation of residuals and why it might negatively impact the quality of our model. I however dont see much info on how to mitigate the bad effects of these ...
0
votes
0answers
39 views

What causes bands/stripes in residual plots?

I ran a model and got the following residuals: I proceeded to log the fitted values to get an idea of what's happening at the lower end of my predicted values: It was then I saw on the left side ...
1
vote
0answers
6 views

When should we use Absolute Deviance Residual Plot or Deviance Residual Plot?

My lecturer mentioned that Absolute Deviance Residual Plot is better to use than the Deviance Residual Plot when analyzing fit of model in the GLM process. I was wondering what do you guys think about ...
2
votes
0answers
36 views

Residual's plot interpretation

These are plots created in R. All of them are residuals (errors) vs. fitted values. They come from multiple linear regression models fitted by least squares. The five plots represent 5 different ...
0
votes
0answers
14 views

TReading Residual Plot: Omitted Variable Bias of Dummy Variable

I have a plot of the residuals versus fitted values of an OLS model such that the shape of the plot are two identical randomly scattered clouds, one above and one below the $\hat{e} = 0$ line. Can I ...
0
votes
1answer
54 views
0
votes
0answers
25 views

Estimating Studentized Residuals (or Another Similar Measure) After Linear Regression With Robust Standard Errors

I have estimated a linear multiple regression with robust standard errors using Stata (regress depvar indepvar1 indepvar2 indepvar3 indepvar4 indepvar5, robust). ...
0
votes
0answers
15 views

Does it make sense to standardize residual using $SSE/(n-1)$?

See[Dean and Voss]Design and Analysis of Experiments,1999. pp.105 The authors proposed that we standardize residuals using: $$z_{it}=\frac{\hat{e_{it}}}{\sqrt{ssE/(n-1)}}$$ where ...
0
votes
0answers
23 views

Analysis of charts

Let $X$ a variable that represents the performance of a student in high school and a variable $Y$ representing the performance of this same student at the university. Consider the regression ...
4
votes
3answers
175 views

Residuals in regression should not be correlated with another variable

This minitab post on checking residuals says: If you can predict the residuals with another variable, that variable should be included in the model. I would think if we can predict residuals ...
2
votes
2answers
170 views

GLM diagnostics and Deviance residual

From my understanding, the deviance residual of a GLM model, when plotted against the fitted values, should give a scatterplot distributed with mean 0 and constant variance? Does this hold for any GLM ...
1
vote
0answers
57 views

Diagnostics and residual analysis for Poisson regression

Recently, I was asked to check for serial correlation after doing a panel Poisson regression. I haven't seen such a test and in general, researchers (at least in the econom(etr)ics literature) don't ...
1
vote
1answer
1k views

How exactly are standardized residuals calculated

I'm working on a model for something and at the moment I prefer working solely in Excel. I've been double checking the results of the linear model in JMP, Minitab, and Statistica, and (more or less) ...
1
vote
0answers
44 views

Plotting and interpreting residuals in Stata - How to identify a structural break?

I am researching firm level data with Stata 13. My endogenous variable is (unfortunately only) of binary nature and indicates whether a firm engaged in R&D activities or not (0;1). I use a panel ...
0
votes
2answers
74 views

I am running a logistic regression model and get very low predicted probabilities

I am running a logistic model for catastrophic health expenditure (CHE) in Argentina. The sample size is 22500. I followed Xu et al. methodology to define CHE and adjusted for 8 socioeconomic ...
4
votes
4answers
397 views

How can I test a nonlinear vs a linear regression model?

I've got a panel regression model where the Ys assume a curved shape when plotted over time. A histogram of the residuals shows they are normally distributed but a residual-vs-fitted plot shows a ...
0
votes
1answer
152 views

Residual diagnostics after a logistic regression model [duplicate]

I wonder about how the residuals of a logistic regression model should be distributed. Of course, running a linear regression model and by assuming the Normal distribution assumption, the residuals ...
13
votes
2answers
717 views

Residual plots: why plot versus fitted values, not observed $Y$ values?

In the context of OLS regression I understand that a residual plot (vs fitted values) is conventionally viewed to test for constant variance and assess model specification. Why are the residuals ...
2
votes
2answers
178 views

Interpreting linearity in residual vs. fitted plot

I am working on a linear regression model and I am not sure how to interpret the following residual vs fitted values plot. For all I know residuals are supposed to fluctuate randomly around 0 ...
0
votes
1answer
56 views

Can heteroskedastic residuals be justified by variance in dependent variable?

This is a very basic question and I hope it is not a duplicate. Im using a pooled regression model with a log-transformed dependent variable (electricity consumption meter values). The variance of ...
2
votes
2answers
183 views

How to verify a linear model?

Given a dataset and liner model, how can I verify its sufficient quality? ...
0
votes
1answer
60 views

Goodness of regression model

What are the main indicators of goodness of a regression model? Are they MSE (mean squared error) http://en.wikipedia.org/wiki/Mean_squared_error , R-squared and adjusted R-squared only? Can mean of ...
0
votes
0answers
250 views

How to use residual analysis to remove the effect of confounding variables in a model in R

I want to find which soil variables better explain plant productivity, using a database that contains information for about 100 forests plots across Europe. These plots have only one species per plot, ...
0
votes
0answers
32 views

Degrees of freedom with duplicate data points

The degrees of freedom of the residual in an OLS model is $n - p - 1$, where $n$ is the number of samples, and $p$ is the number of independent variables. I.e., the data matrix $X$ is $n\times p$. If ...
0
votes
0answers
145 views

Arima Models Diagnostics

I'm doing a forecasting using seasonal ARIMA method. I'm using astsa package in r and I'm testing two models that I can't decide which one is better to use than the other The ACf and PACF for the ...
2
votes
0answers
57 views

Heavy-tailed errors in mixed-effects model

I'm relatively new to statistical modelling and `R', so please let me know If I should provide any further information/plots. I did originally post this question here, but unfortunately have not ...
2
votes
1answer
249 views

Interpreting case influence statistics (leverage, studentized residuals, and Cook's distance)

I just wanted to clarify some things about leverage, studentized residuals, and Cook's distance: Does a large (in absolute value) studentized residual mean that a case is an outlier? Does a large ...
3
votes
1answer
95 views

What if a transformed variable yields more normal and less heteroskedastic residuals but lower $R^2$?

I am trying to decide whether to use a square root transformed dependent variable in multiple linear regression. Transforming $y$ leads to more normally distributed residuals and also to less ...
1
vote
1answer
60 views

Analysing the residuals themselves

As far as I know, it is possible to fit a linear regression model and then fit a second model to predict the residuals from the first model by using some other variables. By this you can understand ...
1
vote
1answer
225 views

Not sure about the interpretation of this residual plot

I'm analyzing a residual plot of the residuals vs the fitted values. I'm not quite sure how to interpret this plot since there looks like there is a pattern and the average is not actually zero. ...
2
votes
1answer
72 views

What is the benefit of knowing the F statistic in multiple linear regression?

One of the basic figures you get when running multiple linear regression using almost any off-the-shelf software is the F statistics. However, I cannot recall one situation, where the F value was low ...
2
votes
1answer
88 views

Multiple Regression - Residual Analysis

I am doing a multiple regression analysis regressing GPA against several 0/1 indicator variables (representing course completions). My fitted vs. residual plot is biased and looks awful. See below. Is ...
4
votes
2answers
3k views

How to perform residual analysis for binary/dichotomous independent predictors in linear regression?

I am performing the multiple linear regression below in R to predict returns on fund managed. reg <- lm(formula=RET~GRI+SAT+MBA+AGE+TEN, data=rawdata) Here ...
3
votes
1answer
73 views

How to perform residual analysis for weighted linear regression?

How do we perform residual analysis (verifying homoskedasticity, normality and independence of errors) for weighted linear regression? By weighted, I mean each row in the dataset has weight assigned ...
2
votes
1answer
122 views

Exponential regression residual check

If you have an exponential regression of the form log(y) = b0 + b1x with predicted equation ลท = 10^(b0 + b1x) and you need to ...
2
votes
3answers
863 views

What kind of residual plot does this variable have?

I am doing a multiple regression analysis and my focus is finding the best set of independent variables for prediction. I am starting to know my dataset and the behavior of each variable. I am doing a ...
3
votes
3answers
531 views

How does the inclusion of an intercept change the variability of the residual?

I want to use the variability of the residual as a measure M and then test whether M is higher or lower after some event. However, I estimate separate regression before and after the event to obtain ...
0
votes
1answer
146 views

Multlinear regression: analysis of residual of transformed response and predictor variables

In the first step of modeling a regression equation I came up with the following model: $T_c = 26.73 + 0.042{\rm Sc} + 0.247{\rm Lc} - 14.709{\rm Lf} + 1.41{\rm Lu} - 0.214{\rm Fc} + 0.041{\rm Ad} - ...
6
votes
2answers
7k views

R - Confused on Residual Terminology

Root mean square error residual sum of squares residual standard error mean squared error test error I thought I used to understand these terms but the more I do statistic problems the more I have ...
4
votes
1answer
899 views

Residual plot for nonlinear regression

I have a couple of questions regarding performance of nonlinear regression models. Are the residuals from a nonlinear regression model supposed to be randomly distributed too (as in linear ...
3
votes
1answer
69 views

Non-constant standard deviation in residuals

I am fitting a model in the frequency domain, and my fit looks as follows: As you can see, the model function does not fit the data perfectly, especially in the higher frequencies. So, I examined ...
1
vote
0answers
166 views

Goodness of fit for orthogonal least square regression

We have a set of XY coordinates which we have fitted with an orthogonal least square regression model. We have a vector of residuals for each point and the fitted line. How do we assess goodness of ...
3
votes
1answer
232 views

validity of regression assumptions on residual plot

I am learning regression course.For a homework given the residual plot I have to analyze it.This is how I interpreted it.I want to know if there are any wrong interpretations. 1)Since the variability ...
1
vote
0answers
105 views

Minimizing the sum of squares of autocorrelation function of residuals instead of sum of squares of residuals

I am trying to fit my multi-exponential model to some experimental data and I am using a simulated annealing algorithm. My objective function has so far been the sum of squares of the residuals: ...
1
vote
1answer
877 views

Outlier detection in ARIMA model with R

After fitting my time series with an ARIMA model, I want to test outliers in the residuals' series. Are there any functions in R that could do this test and furtherly test whether the outlier is ...
2
votes
1answer
1k views

Non-normality of residuals in linear regression of very large sample in SPSS

I have a dataset of ~17,000 cases in SPSS 21 with which I am trying to run multiple linear regression. I have plotted the Studentised residuals against the unstandardised predicted values and also ...
1
vote
1answer
87 views

How to describe the failure of this linear modelling?

I have a time series $X_t$, which is shown in the first plot. In the second plot, I am doing a linear regression on $X_t\sim X_{t-1}$. The regression line is very close to $y=x$. But this is tricky ...
4
votes
1answer
133 views

Why are residual plots constructed using the residuals vs the predicted values?

I am interested to know why residual plots are plotted with residuals against predicted variable of y and not against y?