# Questions tagged [least-squares]

Refers to a general estimation technique that selects the parameter value to minimize the squared difference between two quantities, such as the observed value of a variable, and the expected value of that observation conditioned on the parameter value. Gaussian linear models are fit by least squares and least squares is the idea underlying the use of mean-squared-error (MSE) as a way of evaluating an estimator.

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### The statement of homoscedasticity of variance when describing the OLS model

In an applied econometrics paper, the author states the model to be estimated as: Why does the author claim homoscedasticity? This isn't making sense to me; can't the population variance-covariance ...
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### How to control for market return in an (SPSS) OLS?

Please consider the following panel dataset: ...
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### “Least square root” fitting? A fitting method with multiple minima

I am looking for the name of a fitting method that will work even if points from multiple dataseries are meshed together. As far as I understand there are two major methods, least squares and least ...
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### SPSS dummy variables in OLS

I have a timeseries dataset holding stock data for a large set of companies. Assume the following subset, where obsDay is the observation day (148 days in reality) ...
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### SAS for regression with categorical and quantitative explanatory variables

I am analyzing growth over time for 5 different cultivated forms (cultivars) of maize. Graphing the data reveals a clear linear pattern for all the cultivars in the time interval I am interested in. ...
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### How can I minimize this least squares problem with inequality constraints?

I have a least square problem with two different inequality problems. I can not use NNLS because its just solves least square problem with equality and inequality problems or just one inequality ...
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### What to do when ovtest and linktest in Stata suggest model misspecification?

I have a sample that consists of 50 observations. The base model of the OLS-Regression with three control variables, two of them significant, has a $R^2=0.50$ and its F-Value is 7. Both ...
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### Fitting a continuous result to categorical predictors semiparametrically

Suppose one has a relatively large number of observations, each of which consists of a continuous result and a small number (2 or perhaps 3) of categorical variables, each of which has a large ...
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### Why is semipartial correlation cited so seldom?

In OLS regression, I find the semipartial correlation (a.k.a. part correlation) to be a very useful indicator. When squared, it shows each predictor's unique contribution to explained variance in the ...
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### Predictive power (or $R^2$) adjusted for certain variables

I will frame this question for Ordinary Least Square (OLS) regression, but my question is for both OLS and Logistic. Let's say we data over 10000 different individuals. For each person we have three ...
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### Why is a projection matrix of an orthogonal projection symmetric?

I am quite new to this, so I hope you forgive me if the question is naïve. (Context: I am learning econometrics from Davidson & MacKinnon's book "Econometric Theory and Methods", and they do not ...
Possible Duplicate: Efficient online linear regression Is there a summation representation for multivariate regressions? For example, if I regress $y$ on $X$ instead of using \$\hat \beta = (X'X)^...