The residuals of a model are the actual values minus the predicted values. Many statistical models make assumptions about the error, which is estimated by the residuals.

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Select the cases from a data.frame that have been used in a GLMM [migrated]

I am trying to see differences in the feeding-rate of one bird species between big forest patches and small ones. I have several forest patches of both sizes, and three years of study. Some ...
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1answer
116 views

Are normally distributed residuals not necessarily homoskedastic?

Let's say I've ran a linear regression and I'm checking the model diagnostics. I made a histogram of the residuals and they appear more or less normally distributed as below. I thought for a long ...
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1answer
18 views

How to assess the functional form of covariates in the Cox model with martingale residuals in R?

I want to find if the functional forms of covariates in my Cox model are linear. I understand the way to do this is to plot the Martingale residuals against the covariate of interest. I have found ...
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1answer
70 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. ...
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18 views

Finding the norm of the residual of vector x [on hold]

I am working in matlab and have matrix A and vector b. I have done A\b and produced x, and now am asked to find the norm of the residual using this x. Can someone kinda explain what this means. And ...
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1answer
32 views

How Are Regression Residuals Calculated - Specific Example

I am trying to figure out how regression residuals are calculated using the specific example in the attached graphic. Would I simply B-A (Red letters in graphic) to get C so: 22-30 = - 8 in this ...
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1answer
42 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 ...
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16 views

Residuals plot from ripley K function on spatstat

I am a rookie on R and on spatstat package. I would like some help with the Kres function on spatstat. As is always wise to plot the residuals from any kind of ...
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1answer
68 views

R: test normality of residuals of linear model - which residuals to use

I would like to do a Shapiro Wilk's W test and Kolmogorov-Smirnov test on the residuals of a linear model to check for normality. I was just wondering what residuals should be used for this - the raw ...
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1answer
26 views

Assessing the fit of GLMM implimentation of a Rasch model to binary data using lme4

I'd like to assess the fit of the kinds of models described by de Boeck et al (2011) (http://www.jstatsoft.org/v39/i12). They are GLMM implementation of Rasch family models, e.g.: ...
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2answers
34 views

Beta regression

I have a data set where the response variable Y is a rate between 0 and 1, where the histogram of Y is bimodal. So I feel the linear regression is not suitable.s I have been reading papers about ...
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1answer
32 views

Assessing residuals from a regression model

I am trying to understand what the residuals from a regression convey about the model's adequacy/ability to explain the variance in the data. I read that if we are able to take the residuals from a ...
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2answers
81 views

how to detect outliers from residual plot?

I have the following residual plot. Can I detect outliers from residual plot? I want to remove 200 outliers in my data set, but I do not know how should I do that in R ? residual plots: scatter ...
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1answer
96 views

Does “residual” always imply a positive value?

In the context of calculating standard deviation Wikipedia says that the residual is the difference between an observation and the mean. Is the actual term "residual" referring to an observed ...
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18 views

Testing GLMM residuals against specific families and link functions (R)

When running a GLMM in R with family=gaussian and link=identity, it's easy enough to test whether normality and homoscedasticity ...
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14 views

SLR Residual Plots vs predictor or fitted values?

In our regression class, the professor said we can either plot the residuals vs the predictor values or vs the fitted values. I asked if there was a difference in the two plots (i.e. might you be able ...
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17 views

Mean in Cumulative frequencies distribution

Monthly expense Cumulative Freq. up to 50 7 up to 80 25 up to 120 49 up to 200 58 over 200 60 Calculate ...
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15 views

interpret regression slope of residuals against an independent variable

I did a linear regression of crop yield against year and took the residuals of this regression for my further analysis ...
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1answer
36 views

Exponential regression residual check

If you have an exponential regression of the form log(y) = b0 + b1x with predicted equation ŷ = 10^(b0 + b1x) and you need to ...
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31 views

How to interpret residual vs fitted values plot with clustered points

I am performing a multiple linear regression and I have a plot of the my first two explanatory variables vs the residuals and also a plot with the residuals vs the fitted values. I am not quite sure ...
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1answer
40 views

SLR: Variance of a residual

I am having problems calculating the variance of a residual in an SLR setting, ie $\text{var}$$(y_i- \hat{y_i})$. Here is what I have thus far. If $ \hat{y_i}= \hat{\beta_0} + \hat{\beta_1}x_i$ ...
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35 views

Controlling for categorical variables before correlation using residuals?

I’m looking for a way to control for the effect of multiple categorical variables, all of which contain two independent categories, on two continuous variables before I correlate these continuous ...
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1answer
48 views

Residual Plots and Transformations in Linear Regression

What does it typically mean when the plot of residuals vs. fitted values in a linear regression forms a parabola symmetric about the y-axis (for both convex and concave parabolas)? How can one infer ...
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318 views

In simple linear regression, where does the formula for the variance of the residuals come from?

According to a text that I'm using, the formula for the variance of the $i^{th}$ residual is given by: $\sigma^2\left ( 1-\frac{1}{n}-\frac{(x_{i}-\overline{x})^2}{S_{xx}} \right )$ I find this hard ...
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Struggling with non-normality in generalized linear model

Dear statistics experts, I am looking for correlations between certain measures of brain structural integrity (fractional anisotropy, given as ratio between two hemisphere ==> rational data range ...
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1answer
44 views

Validating residual plot count data (different levels)

I am studying the distribution of a marine species using the number of sightings as a dependent variable. When I am trying to validate the plots of the best model I am getting a non-usual pattern, and ...
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1answer
51 views

Why the Breusch-Pagan rejects H0 on apparently non-heteroskedastic data?

Breusch-Pagan rejects the H0 on this residuals: ...
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20 views

How to get observations from residuals in an ARIMA model?

If we have residuals of an ARIMA(p,d,q) with known parameters, how can we retrieve the original observations of the time series?
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27 views

Line with discontinuous sigmoid function in half-normal residuals plot

In R, I've plotted the half-normal residuals for a few different models, i.e. halfnorm(residuals(model_object))) I notice that one plot takes a distinct S-shape ...
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56 views

How to interpret residual plots from time series regression

I am doing a time series regression between 2 variables. I used the dynlm library in R. I'm trying to understand how to interpret the results. Could you please point out where I am getting it wrong: ...
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38 views

F-adjusted Mean Residual Test in R

I'm running diagnostics on a logit model in R produced with glm(formula = formula, data = data, family = "binomial"). I'm ...
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3answers
93 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 ...
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11 views

Classification Residual Analysis with rank-based goal

I have a dataset consisting of users, each with a number of items (ranging from 1 to 100). The end-goal is for each user to be able to predict the ranking the of the items according to some other ...
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24 views

Derivation of normalizing transform for GLMs

How is the $A(\cdot) = \int\frac{du}{V^{1/3}(\mu)}$ normalizing transform for the exponential family derived? More specifically: I tried to follow the Taylor expansion sketch on page 3, slide 1 of ...
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1answer
45 views

Non-seasonal periodicity in Time Series residuals

I have been working on a forecast model in Excel extrapolating from a small (150 data points) monthly time series. I've converted into a year/year percentage change series to get it stationary, ...
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Contribution of residuals to the mean error

I have data for 1000 students' performance over 10 different tests on a scale of 0 -100 (a 1000 rows X 10 col matrix). I calculated the mean score and the associated std. deviation for each student. ...
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1answer
48 views

Strange residuals interpretation

I have run a model and with the data I have, I wasn't expecting to produce the best model ever but my residuals are really strange. The outcome variable is number of days going to a website in a month ...
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1answer
77 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 ...
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1answer
44 views

Residual autocorrelation versus lagged dependent variable

When modeling time series one has the possibility to (1) model the correlational structure of the error terms as e.g. an AR(1) process (2) include the lagged dependent variable as an explanatory ...
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1answer
71 views

Working with residuals of regression

So the background is that the I collected yield data for past 5-6 decades and location from where I collected yield data had high yielding varieties introduced over time. I am looking at the ...
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1answer
90 views

What resolution should I be using for residuals vs fitted values plot from a linear regression?

I made this linear regression that shows how well estimated animal locations (longitude) predict actual animal locations. ...
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12 views

How to compare a measure reflected by a regression residual in a pre-post design?

Maybe a simple question, but my head is spinning: I want to see if X increased after a certain treatment in a pre-post study. Unfortunately, I have only K which is a noisy measure of X. To "clean" K ...
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55 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
44 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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24 views

Correlation fitted-residuals in mixed models

IN OLS linear models, fitted (predicted) and residuals scores are uncorrelated. I was under the impression that the same held true in mixed models. However, I have here an example model where fitted ...
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30 views

Use of Deviance Residuals for Leave-One-Out Cross Validation

I am a newbie to stats and having some difficulties understanding how to use deviance residuals for leave-one-out cross validation for a logistic regression model. The problem that I am trying to ...
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1answer
67 views

Durbin Watson test statistic

I applied the DW test to my regression model in R and I got a DW test statistic of 1.78 and a p-value of 2.2e-16 = 0. Does this mean there is no autocorrelation between the residuals because the ...
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1answer
80 views

Poisson Regression Residuals

I'm modeling the number of doctor visits (a count variable) on factors such as income, chronic condition, insurance, etc. I use the canned Stata command ...
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2answers
65 views

Logistic regression and error terms

In logistic regression, if we considered residuals, could they only take on the values $0$ or $1$? The data points themselves take on only $1$ or $0$. The logistic curve can take on any value between ...
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1answer
40 views

What is the method for calculating stdres in {MASS}

The documentation for the MASS package does not detail the calculation method for the standardized residuals using stdres(). I ...