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

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Regression model for predicting life expectancy

I have average life expectancy at birth data for an 8 year period and I would like to use that 8 year period to predict the trend for average life expectancy for the next 5 years. I would then like to ...
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12 views

Shape uncertainty of a 3D point cloud

Given a point cloud of a 3D object, how to calculate the shape uncertainty in this discrete sample set? and what factors maximize or minimize this uncertainty?
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21 views

Why sandwich estimators aren't always used in OLS regression?

I asked before what is the intuition behind sandwich estimators. I must still missing something because I don't understand why sandwich estimators are not always applied to OLS residuals. Can you ...
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16 views

Do assumptions for estimators affect population parameters?

TL;DR: Specifying a model (a collection of restrictions over a sample space) specifies the model parameters. Specifying an estimation procedure adds additional number of restrictions (assumptions?). ...
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18 views

Predicting values using linear regression

I am very new to statistical analysis and R. Recently I worked on a simple linear regression model to predict values. For example: consider the below data set ...
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1answer
15 views

Benchmark datasets for testing multiple regression or multivariate regression model?

I have a question as a newbie. I'm working on a tool using regression analysis( linear, multiple, multivariate) to derive a regression model. To verify the correctness of the tool, I'm trying to find ...
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2answers
83 views

Which is correct way for regression line?

I have a set of data (some Frequencies per month, Var1 is the month): ...
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19 views

Adding predictor variables and/ or systematic judgement to time series forecasts

I have a ways to go with my forecasting general education --- but I'm doing a seasonal time-series forecast for predicting sales order volumes. It's mostly software sales, which does have a ...
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28 views

t test for slope with binary variable

Cosider two random samples: one from the variable $Y_1$, with $n_1$ observations and the other one from the variable $Y_2$ with $n_2$ observations. Let $\mu_1$ and $\mu_2$ be the sample means of ...
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4 views

What is a good model for a regression analysis having TF-IDF dependent variable?

I am trying to build some models for a multivariate regression analysis that have as dependent variable TF-IDF values for some terms extracted from textual documents. An important characteristic of my ...
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19 views

Fitting a model to data for prediction - best choice for data

I have some data I need to fit a model to that can be used for prediction (interpolation). The data is summarized by the plot below. The black line is x=y. I want to be able to fit a model so as I ...
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1answer
38 views

c-index for parametric links in binary regression

I am conducting a binary regression using different sorts of parametric links (logistic, Pregibon, Aranda-Ordaz, ... see) and I would like to compare their predictive and classification perfomance in ...
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1answer
13 views

Suitable function to choose the best split in a regression tree/oblivious tree

My main objective is to construct a regression (decision) tree. It is a part of a boosting algorithm using additive regression trees. The first question is what other functions (other than least ...
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15 views

Standard error for multiple regression? [duplicate]

My understanding of the standard error of estimate for a simple linear regression as a function of the sum of squares over the number of observations, but how do we interpret the standard error for a ...
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11 views

TF-IDF Matrix and Regression

I am trying to build a regression model based on some tweets that my company put on our company feed. I would like to transform all of the tweets, and use them to tell me which word(s) were most ...
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17 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 ...
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30 views

multiplicative model in r

I have to estimate a model forecasting the sales (as stock units) for AXE deoderants.I want to apply the multiplier specification on this model. The model should look like this: log(Sales) = b0 + ...
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1answer
40 views

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

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 ...
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26 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 ...
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1answer
128 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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23 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 ...
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15 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 ...
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1answer
32 views

Multiple regression model

I have a multiple regression equation which as four quarters (maybe called them as parameters) ...
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5 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 ...
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35 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: ...
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1answer
69 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? ...
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30 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 ...
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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 ...
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33 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 ...
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28 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 ...
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1answer
52 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 ...
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3answers
62 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 ...
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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 ...
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24 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 ...
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23 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 ...
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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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27 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 ...
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1answer
40 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?
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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 ...
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1answer
55 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 ...
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1answer
52 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 ...
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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 ...
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1answer
41 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 ...
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22 views

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

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 ...
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20 views

How do I compare different models? [closed]

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 ...
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0answers
19 views

Incorporating outlier points into a unified prediction model [closed]

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 ...
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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 ...
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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 ...
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14 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: ...
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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 ...