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2
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0answers
8 views

Least squares / residual sum of squares in closed form [migrated]

In finding the Residual Sum of Squares (RSS) We have: \begin{equation} \hat{Y} = X^T\hat{\beta} \end{equation} where the parameter $\hat{\beta}$ will be used in estimating the output value of input ...
0
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0answers
22 views

extract residuals from adonis function in vegan

I am using the adonis function in the vegan package to determine effects of different environmental factors in forest plant community composition in different regions. I would like to first use adonis ...
1
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0answers
24 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: ...
0
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1answer
115 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
160 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
75 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 ...
0
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0answers
37 views

If the residuals of each group show same tendency, what does it mean?

I'm doing my reseach paper, and there are 7 groups for 5 years. I'm trying to do "panel gls" in STATA. It's a little embarrassing to say, but I think I still don't have enough konwledge to analize the ...
1
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0answers
64 views

Residuals plots of residual vs predicted variable

I am interested to know why residual plots are plotted with residuals against predicted variable of y and not against y?
0
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0answers
55 views

Augmented component plus residual plots

To test for linearity, it has been suggested that augmented component plus residual plots are the best option (acprplot in Stata). Should this analysis be done for ...
0
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0answers
116 views

Robust Residual standard error (in R)

I have a question regarding to the concept of robust standard errors. What I found about that topic is, that one can estimate the robust standard error for regression coefficients to eliminate ...
0
votes
0answers
65 views

Analyzing residual plot vs independent variables plot

Why do we analyze residual plot in regression analysis and NOT between two individual variables? For example when checking for normality, heteroscedasticity etc. we don't analyze two individual ...
2
votes
1answer
267 views

Multiple testing correction for chi squared residuals

I am running cluster analysis (using mclust in R) and then looking to see whether various known data groupings (based on ...
0
votes
0answers
165 views

Validation of conditional logistic regression model with CoxReg (SPSS): must use residuals from CoxReg?

I have developed a case-control study, matched 1:2, and I have addressed the conditional logistic regression analysis with COXREG (...
4
votes
1answer
369 views

Interpreting a residuals vs fitted plot and extracting points

I'm doing a multivariate linear regression with R, and i find myself with the following residuals vs fitted plot: As you can see there is a very regular line of points that seems to follow a ...
1
vote
1answer
409 views

Reasons for autocorrelation in time-series residuals

Why are residuals usually autocorrelated in time-series data? Could it stem from the autocorrelation of the response variable? Is the reason that in some cases the differencing (i.e., the differences ...
6
votes
1answer
661 views

Sandwich estimator intuition

Wikipedia and the R sandwich package vignette give good information about the assumptions supporting OLS coefficient standard errors and the mathematical background of the sandwich estimators. I'm ...
1
vote
2answers
820 views

In R, how can I transform to normalize residuals when I have a U-shaped Q-Q plot?

I am running a two-way ANOVA with one random variable. My histogram of the residuals is showing considerable (negative?) skew: And my Q-Q plot of the residuals shows a corresponding U-shaped ...
0
votes
0answers
62 views

Hypothesis testing using only RSS

I have been presented with an interesting regression question: Suppose I have a "black box" that will calculate the residual sum of squares: $RSS=(Y-X\hat{\beta})'(Y-X\hat{\beta})$ for any standard ...
11
votes
2answers
14k views

Regression when the OLS residuals are not normally distributed

There are several threads on this site discussing how to determine if the OLS residuals are asymptotically normally distributed. Another way to evaluate the normality of the residuals with R code is ...
13
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2answers
5k views

Interpreting residual diagnostic plots for glm models?

I am looking for guidelines on how to interpret residual plots of glm models. Especially poisson, negative binomial, binomial models. What can we expect from these plots when the models are ...
1
vote
1answer
446 views

Shapiro-Francia test error

I'm trying to run a normality test on the residuals after fitting a mixed-effect model (with lmer). I read that the Shapiro-Francia test can deal with data with more than 5000 observations (I have ...
2
votes
2answers
318 views

Bayesian inference of parameters: residuals are independent but not normally distributed

I would like to compute belief intervals (confidence intervals; CI) for the parameters of an environmental dynamic model within the Bayes' theorem. The measurement model of the data is $$ ...
2
votes
1answer
104 views

Is it ok to bin residuals before examining them?

I'm analyzing the residuals from a regression model fit to a dataset that covers several years worth of data. I want to report the sum of the residuals from that model, by year, as a measure of how ...