Tagged Questions
2
votes
1answer
36 views
Is the exponential distribution a good model for this data?
I'm trying to determine if the exponential distribution is a good model for a data set that I'm exploring. It doesn't have to be precise. I'm using the data for capacity planning (if it's a good fit) ...
0
votes
0answers
35 views
How to compare 2 regression slopes with R?
I have to compare the slopes of 2 regression lines with R. The 2 regressions are made with the same parameters in 2 different locations.
I did my regressions with the function lm(). Now I have the ...
1
vote
0answers
22 views
R module for creating plots of prototypical individuals from fitted models?
In order to help interpret fitted models — especially those with interaction terms and non-linear components — I've found it useful to plot predicted values of a dependent variables for what we might ...
0
votes
2answers
76 views
How to interpret the output of the summary method for an lm object in R? [duplicate]
I am using sample algae data to understand data mining a bit more. I have used the following commands:
...
3
votes
0answers
34 views
How to build a model where variance depends on covariate?
I have what I believe is a very simple problem for anyone used to modelling with unequal variances (which I am unfortunately not). I have a dependent variable "totrich" which I want to model as a ...
0
votes
1answer
34 views
Weighted multiple regression in R with prespecified weights
I would like to run a regression of the following form:
Y ~ B1*predictor1 + B2*predictor2 + B3*predictor3
I would like to specify ...
0
votes
1answer
40 views
Basic questions concerning the interpretation of results from summary(lm(…~…)) in R [duplicate]
set.seed(11)
a = runif (12)
b = rep(c(1,2,3),4)
summary(lm(a~b))$coeff
summary(lm(a~b-1))$coeff
What does a p.value for the intercept means ?
What differences ...
0
votes
0answers
20 views
Strategy for building best fit multiple regression model with time lagged variables
I am building a multiple regression model - wrapped in a function - with one dependent variable and a dozen independent variables. The reason why I am building a function is that I need to do this ...
2
votes
3answers
70 views
Which glm algorithm to use when predictors are numerical as well as categorical?
I just need a direction on which regression algorithm (preferably glm or similar) algorithm to use when the predictor variables are a mix of numerical and categorical variables. The output is ...
0
votes
1answer
76 views
Multiple Choice on Linear Regression
1. Which one is NOT a linear regression models? Please give a 1-2 sentences brief
explanation to your choice.
(a) $y_i = β_0 +\exp(β_1x_i)+E_i, i = 1, 2, \ldots, n$
(b) $y_i = β_0 + β_1x_i + β_2 ...
3
votes
1answer
45 views
Hold-one-out linear regression : a shortcut?
For a series of observations $(\vec{x}_i, y_i), i = 1 \cdots N$ from the linear model $Y = \beta^T X + \epsilon$, the least squares estimate of $\beta$ is: $\hat{\beta} = (\mathbf{X}^T ...
3
votes
0answers
34 views
Brant test in R
In testing the parallell regression assumption in ordinal logistic regression I find there are several approaches. I've used both the graphical approach (as detailed in Harrell´s book) and the ...
2
votes
0answers
16 views
Non-integer dependent variable in negative binomial models
I have non-nested count data that I've interpolated from one area to another based on the proportion of the area that lays in each. This is ZIP codes to counties, so most nest cleanly, with a few ...
-3
votes
1answer
65 views
Calculating the linear model with R
I need to calculate the linear model in R, i did the following:
summary(model)
But what if I wanted to calculate only the first point? A bit stuck with this one... Many thanks!
Here is the code ...
1
vote
0answers
23 views
Nested vs. conditional logit regression
I am trying to estimate a logit regression model with travel mode choice (categorical) being the dependent variable; explanatory variables include age (categorical), income (categorical), gender ...
0
votes
0answers
23 views
Setting indicator variables to equal 1 or 0 [migrated]
I have to set HIGPA to equal 1 if the gpa is greater than 3, and if it is less, then HIGPA must equal 0. I am using R.
gpa is already a variable in the data. HIGPA is not.
So far I have made HIGPA a ...
2
votes
2answers
217 views
1
vote
0answers
27 views
Ways to find a confidence interval for robust and quantile regressions
I'm trying to compare a few regression models for my data. For linear regression everything is quite understandable, but robust and quantile regressions are not so obvious. I could not find almost ...
2
votes
1answer
61 views
Advice on the statistical analysis of clinical data using summary statistics, t-tests, ANOVA, and linear regression
I need some help with the statistical analysis of a study of a particular surgery to remove a particular cancer. I am using the statistical program R to conduct my analysis. My data are saved in the ...
2
votes
0answers
32 views
How to report most important predictors using glmnet?
I want to find the most important predictors for a binomial dependent variable out of a set of more than 43,000 independent variables (These form the columns of my input dataset). The number of ...
0
votes
0answers
16 views
How to get all points for a fitted spline in R? [migrated]
I am trying to find the MSE of a fitted smooth.spline in R (and compare it with other methods) using a default data set (cars). ...
0
votes
0answers
28 views
OLS in Python with Dummy Variables - Best Solution? [migrated]
I have a problem I am trying to solve in Python, and I have found multiple solutions (I think) but I am trying to figure out which one is the best. I am hoping to choose libraries that will be ...
0
votes
0answers
29 views
regression: handling negative autocorrelation in R?
I am running a regression in the R package nlme (but am not constrained to only that package). I am changing the spatial scale of the analysis over a few regression runs as a form of sensitivity ...
3
votes
0answers
39 views
Interpreting plot(lm)
I had a question about interpreting the graphs generated by plot(lm) in R. I was wondering if you guys could tell me how to interpret the scale-location and leverage-residual plots? Any comments would ...
0
votes
0answers
21 views
How to calculate Hightest Posterior Density (HPD) of coeficients in a simple regression (lm) in R?
I am trying to calculate HPD for the coeficients of regression models fitted with lm or lmrob in R, pretty much in the same way that can be accomplished by the association of mcmcsamp and HPDinterval ...
1
vote
2answers
43 views
Dealing with grouped / rounded data
I have a dataset that includes variables about customer income levels. The income was collected in binned fashion (...
0
votes
0answers
36 views
Standard deviation of errors
I have a multiple regression model (information derived from gretl):
$$Y=‐3,859921 \ln(P)
+
1,707514\,
(A)
+
3,578656$$
$$\quad\quad\space(1,216387)\quad\quad\quad(1,259650)\quad\quad(0,323867)$$
...
1
vote
1answer
47 views
Cauchy M estimator of regression in R
Was wondering if anyone knows of an R package to estimate the Cauchy-M estimator of regression (see for example the end of this section, but with simultaneous estimation of the scale parameter as in ...
3
votes
1answer
39 views
(Prediction) constrained OLS in R
I have a collection of $n$ datapoints $(y_i,\bf{x}_i)$ in $\mathbb{R}^{p+1}$ and would like to estimate the following model in R:
...
4
votes
1answer
73 views
Calculate mean of one variable while controlling for another using regression
This is probably a very naive question... I'd like to estimate "adjusted" or "conditional" means for a variable (i'm unsure of the correct terminology). My data are on cortisol levels (dependent ...
0
votes
1answer
72 views
Question about reading an output for using ANOVA to compare two linear models
I tried to compare the following two models using "anova.lm()" in R:
...
0
votes
1answer
49 views
When is it valid to include interaction terms in a regression model? [duplicate]
I am using logistic regression to analyze some categorical data (binary response variable and categorical -- mostly binary -- predictor variables). For my model, I have something like ...
3
votes
1answer
141 views
Interpreting interaction terms in logit regression with categorical variables
I have data from a survey experiment in which respondents were randomly assigned to one of four groups:
...
0
votes
0answers
42 views
Energy estimation through machine learning
Greedings to everybody.
I have the dataset which you can find here, containing many different characteristics of different houses, including their types of heating, or the number of adults and ...
1
vote
3answers
113 views
how to interpret the interaction term in lm formula in R?
In R, if I call the lm() function in the following way:
lm.1 = lm(response ~ var1 + var2 + var1 * var2)
summary(lm.1)
This ...
2
votes
1answer
118 views
3
votes
1answer
47 views
Recreate logistic regression equation from table of odds data
I'm reading the technical manual for a linking study between two assessments. It's pretty clear that the table is model output from a fitted logistic regression equation. Here's what pass odds look ...
0
votes
0answers
23 views
Cross-validation of a SMA (standardized major axis regression) model
How to cross-validate a standardized (reduced) major axis regression (SMA) model in the Smatr package (this package has no predict function)?
I have used boot, bootstrap, DAAG, cvTools, rms and Zelig ...
-1
votes
4answers
106 views
How do I get better forecasts for this data
How do I get better forecasts for my model? Is the plot supposed to look like this? I am using the code:
fit <- auto.arima(blah)
fcast <- forecast(fit,100)
...
4
votes
1answer
189 views
Meaning of p-Value of logistic regression model variables
So I'm working with logistic regression models in R. Though I'm still new to statistics I feel like I got a bit of an understanding for regression models by now, but there's still something that ...
0
votes
3answers
76 views
Regression for a Rate variable in R
was tasked with developing a regression model looking at student enrollment in different programs. This is a very nice, clean data set where the enrollment counts follow a Poisson distribution well. I ...
1
vote
1answer
44 views
Standard Error of Standard Deviations Estimated with gls in R
In the gls fit shown below, the estimates of the standard deviation for each level of X are apparently given by the product of (1.000000, 3.913972, 10.684698, 11.350910, 26.476561, 27.255072) times ...
1
vote
0answers
49 views
Interpretation of Translog regression
I'm a beginner in R and Im wondering how to interprete my results.....
My question is about the results that I got after I did a regression on the Translog production function for panel data:
$ ...
0
votes
0answers
34 views
Problem with lqmm. Very long time to run and issues with error handling
I am trying to use lqmm to fit some models and it appears to be working ok with my data (N 2000 w/ clusters=1200). I am using a call like this:
...
0
votes
0answers
25 views
Compare the predictive power of a model between datasets
I have two sets of continuous response data for the same group of species, but in different areas (area a and area b). I am building a model for each area separately, to predict the area-specific ...
5
votes
1answer
185 views
Wald test in regression (OLS and GLMs): t- vs. z-distribution
I understand that the Wald test for regression coefficients is based on the following property that holds asymptotically (e.g. Wasserman (2006): "All of Statistics", pages 153, 214-215):
$$
...
0
votes
0answers
61 views
How big of a dataset can R or SAS handle for regression?
On a standard computer (~3-6gb RAM) with 2 - 4 processors.
What are the size restrictions on a matrix of data for R or SAS?
1
vote
1answer
57 views
How to interpret a non significant independent variable?
I conducted a regression analysis using R's lm() function. One of the independent variables shows no significance (p = 0.89), which contradicts the hypothesis that is should have a significantly ...
0
votes
1answer
72 views
Variable Selection in R: Choosing One Variable from Each of 3 Buckets of Variables
I have a regression model that looks like the following
glm.nb(formula = y ~ Gender + Age + x1 + x2 + x3, data = df)
In my problem, there are 20 possible choices ...
1
vote
0answers
60 views
Is LOESS the appropriate way of visualizing my RT data?
I am conducting a Lexical Decision Task where my dependent random variable is Response Time (RT).
My experimental design consists of 5 blocks of a 100 trials each. In each block, 50% of trials ...
