Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

learn more… | top users | synonyms (1)

0
votes
0answers
10 views

Regression Modeling with Upper and Lower Bounds on target distribution

I am trying to run a simple regression model between a couple of variables, one of which is bound between values of (.25 - .75). This will be my target variable. I understand the beta distribution can ...
2
votes
1answer
37 views

Is mean centering required in regression? if so, what does it do?

Let say we have a dataset, $\mathbf{X}$ of $m$ instances, and $n$ features, and a target scalar variable $\mathbf{y}$ ($m$ instances). Now I want to do a regression so, I try to fit a hyperplane $ y ...
0
votes
0answers
21 views

What does hat matrix mean? [duplicate]

$$H= X(X'X)^{-1}X'$$ I understand that if we multiply $Y$ matrix by $H$ matrix, then we will have $\hat Y$. That's why we call it $H$ matrix. Can someone please let me know what $h_{ii}$ ($i$-th ...
4
votes
1answer
104 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 ...
0
votes
0answers
9 views

Trying to understand the basics of a mixed-effects logistic regression model for a 10-step continuum

I am trying understand how to correctly build a mixed-effects logistic regression model in R. I believe my model is pretty simple and straight forward but I'm lacking in experience and uncertain I'm ...
2
votes
0answers
9 views

Correlation on ordered subset

Imagine a hypothetical scenario in which a ball is thrown along a straight line. During flight, the position is continually sampled; however, at some distance, the sampling fails and only noise is ...
0
votes
1answer
27 views

Multiple regression model

I have a multiple regression equation which as four quarters (maybe called them as parameters) ...
0
votes
0answers
3 views

pggls function in R - weird results

I need to estimate a panel model. I have run the "normal" fixed effects model using plm in R and also wfe. I also wanted to try pggls considering its tolerance of heteroskedasticity and ...
1
vote
0answers
28 views

Linear model / models analysis

Above are three plots of the Linear model I am trying to analyze. The first one is a basic plot of the linear data: ...
0
votes
1answer
60 views

Theories how they arrived at this Ebola growth forecast? Not regression

The 21,000 estimate for Oct. was certainly not via quad or power regression. I wonder how they got that number? ...
0
votes
0answers
27 views

I get unusual (wrong) results when plotting regressions with log10 axes compared to linear axes [on hold]

When plotting a datasets of values and then using linear regression I get different (unexpected and seemingly wrong) results when plotting using log10 on both axes. Can someone please help. OK code ...
0
votes
0answers
10 views

Thorndike Case 2

I'm currently working on university data that, due to the competitiveness of the selection for certain degrees, appear to be displaying range restrictions. For example, for one particular degree the ...
0
votes
0answers
26 views

Gaussian mixture vs. Gaussian process

As far as I know, both Gaussian mixtures as well as Gaussian processes can be used for regression. My question is: what is better and why? The answers might contain theoretic insights, practical ...
1
vote
0answers
23 views

Building a predictive model, regression with a long right tail

I am trying to build a, regressive, predictive model for a target time-series that is heavily skewed. You could think of the target as being like earthquake magnitudes or heavy rainfall. Most of the ...
0
votes
1answer
46 views

When to use bootstapping in regression analyses?

When I run a regression analysis in SPSS, one of my predictor variables just fails to reach significance, p = .06. When I apply bootstrapping, the output tells me the predictor has a significant ...
-1
votes
2answers
45 views

How to analyze relationship between data pairs

Please change the title if it's not accurate, I might be lacking terminology. I have two variables (x,y) which are directly correlated by pair. For example I have sampled 50 trees in my study area ...
0
votes
0answers
13 views

Regression using a priori knowledge

I am sorry if the title (and probably the question) is not very clear but I have a regression problem which might be a bit over my head if I want to do it well. I am only interested in getting some ...
1
vote
0answers
20 views

Analysis of a longitudinal study where interventions are received at different time points

I have a data set of university students. The university has 8 different assisting programs, mostly like scholarships, for needy students to help them concentrate on their studies. Since it costs a ...
0
votes
0answers
21 views

mixed effect regression model

I would like to expand over a previous question of mine (What is the correct model for this experiment design?), with slight modifications... To set up the scene : We have a completely randomized ...
1
vote
1answer
68 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. ...
0
votes
0answers
22 views

Phylogenetic General Least Squares, Multivariate Regression

I'm working on a biological question, with species data derived from an external database, which has multiple response and predictor variables. As a result, I want to do multivariate regression across ...
0
votes
1answer
37 views

Selection of regressors into a regression model

Why is it that backward selection/elimination as compared to forward selection of regressors, is often less adversely affected by the correlative structure of regressors?
1
vote
1answer
43 views

Choosing predictor for regression

If a predictor is almost the same as the criterion (different tests measuring same domain and they are both highly correlated) would that predictor be worth-including in the regression model? What if ...
0
votes
1answer
49 views

R regression difference between factor and numeric

I have a set of data that I am using regression analyses on. All of the columns are numeric (as far as I can see) a mix of integers and reals. However, two of the columns are being read from the CSV ...
3
votes
1answer
42 views

How to efficiently compute Theil-Sen estimator?

The Theil-Sen estimator is of interest to me, however when I implement it myself I end up with something that scales as O(n^2). According to wikipedia, it can be calculated exactly in O(n log(n)). Can ...
0
votes
0answers
5 views

How can Durbin-Watson and SPEC give Opposite Results?

I am modelling house prices against sales amount using a simple linear regression model. My SPEC (Option in SAS) says IID (p-value > 0.05) but my DW (Option in SAS) says a strong 1st order ...
1
vote
1answer
28 views

Probability distribution of Y in regression?

I'm trying to predict the probability distribution of $Y$ given $X_0, X_1, ...$ with a nonlinear regression. The probability distribution of $Y$ is likely not normal. So far, I've set up and trained ...
0
votes
0answers
19 views

Correlation? Factors affecting academic performance of students based on their gpa? [on hold]

My friend's thesis. just helping her with the data analysis "FACTORS AFFECTING ACADEMIC PERFORMANCE OF STUDENTS BASED ON THEIR GPA" Divided it into: Internal Factors: Class Schedule & parental ...
0
votes
0answers
20 views

How do I compare different models? [on hold]

I have four different models with a different amount of significant variables. One is a simple linear model, one is logarithmic, one is logarithmic with a saturation rate and the last includes a ...
0
votes
0answers
19 views

Incorporating outlier points into a unified prediction model [on hold]

There is a data set including multiple outlier points. If we want to build a regression model based on these points, what are the general approach to handle these outlier points? Are there any good ...
0
votes
0answers
18 views

The way to evaluate the importance of an independent variable in a regression model

In a regression model, like y~( x1, x2, x3). Is there a test or a way to evaluate which independent variable, x1, x2, or x3, is ...
7
votes
5answers
179 views
+50

What exactly are censored data?

I have read different descriptions of censored data: A) As explained in this thread answer, unquantified data below or above a certain threshold is censored. Unquantified means data is above or below ...
0
votes
0answers
13 views

Auto.arima choose between lots of regressors

I have to forecast data with two seasonality with ARIMA. I find that I have to use a code like this: ...
1
vote
0answers
17 views

Distinguishing between different notions of $R^2$

What is the distinction between $R^2_{pop}$ – the population R-squared $R^2_{out}$ – the out-of-sample R-squared $R^2_{c.v.}$ – the squared population cross-validity coefficient ? These ...
0
votes
1answer
50 views

Linear regresson lm or stepwise regression here using R?

It is a basic question but I could not find clear answer on my reading. I am trying to find independent predictors of Infant.Mortality in data frame 'swiss' in R. ...
0
votes
1answer
10 views

Generating Regression For Unknown Beta in Matlab

My professor wants me to generate a regression problem based on the following: B is fixed unknown 100,100 matrix, X is random 100,100 matrix and y and noise are a random scalar for every output. He ...
3
votes
3answers
98 views

How to fit regression to custom model in R

This is for my honors thesis. I have a large data set, of which I'm sharing only what I call the "Low phosphorus" series: ...
0
votes
0answers
11 views

Run Tobit with missing values (from linear prediction) or change them to zeros - STATA “practical” question

I want to run a Tobit linear regression in order to especify a labor-supply curve (linear-linear). As dependent variables I have personal characteristics, enviromental ones, and wages (predicted using ...
0
votes
1answer
26 views

Modelling interaction

How does adding interaction term in the model adjust for it or why do we need to add interaction? I am working on logistic regression model with treatment and race as predictors. I have added ...
2
votes
2answers
36 views

Fitting decaying exponential to binary response

I have this data that I want to fit with $y = e^{-bx}$, but the y:s represent probabilities and the outcomes are either 0 or 1, so I can't say $ln (y) = -bx$ since the values will just alternative ...
3
votes
1answer
70 views

Sample $R^2$ consistent?

In a linear regression context: is the sample $\widehat{R^2}$ a consistent estimator of the population parameter $R^2$? Maybe this depends on distributional assumptions?
1
vote
0answers
12 views

When to use skew normal regression via MCMC (mixture models)?

when do i use skew normal or skew t Regression via MCMC? Do I use them when the data are heavily skewed, for example income data? Or do I fit a normal Regression model first and inspect the residuals ...
0
votes
0answers
12 views

algorithm to predict cost function

The goal of problem is to predict the weight for missing data . I have a dataset of categorical type as shown below ...
2
votes
2answers
150 views

When can a continuous variable be treated as categorical?

I have a continuous variable, which can take any value between 0 and some large, though not infinite, number. Let us assume that the maximum possible value is 1000. The values are nowhere near ...
2
votes
1answer
37 views

Interpretation of logged regression

I have run a linear regression with the following equation (in r): lm(formula = logTotal ~ Continent + logArea + Method + Servs) where ...
0
votes
0answers
28 views

Predictive model with combinations of dummy variables of different length

I would like to try to predict the amount of a public contract based on historic records where the main variables that I can fit against include: contact duration (continuous) number of buyers ...
0
votes
0answers
11 views

Combining outputs from multiple regressions

I have a sample N with K independent variables (and 1 binary dependent variable) Of this K, a number (L) are avaliable for all of N. Of the rest (K-L), different subsets of N have different sets of ...
1
vote
1answer
38 views

3D surface plot for least square & ridge regression

I'm very impressed by this plot: Why does ridge estimate become better than OLS by adding a constant to the diagonal? Does someone has any clue about how to plot this on R? I mean, how to get RSS ...
0
votes
0answers
33 views

Stochastic Gradient Descent for Logistic Regression always returns a cost of Inf and weight vector never gets any closer

I am trying to implement a logistic regression solver in MATLAB and i am finding the weights by stochastic gradient descent. I am running into a problem where my data seems to produce an infinite ...
0
votes
0answers
17 views

Regression using indicator variables and time t. (R code) [duplicate]

I'm having difficulties setting regression R code.... This is the data that I need to use: ...