# linear model

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## linear model

[′lin·ē·ər ′mäd·əl]
(statistics)
A mathematical model in which linear equations connect the random variables and the parameters. Also known as linear hypothesis.
References in periodicals archive ?
Durbin-Watson (DW) tests for first order autocorrelation showed nearly all of the price series studied had strong autocorrelation necessitating the generalized least squares procedure.
Table 2 Model Coefficient Estimates for the Sample of 234 Corporations for the Years 1977 through 1994 using the Random Effects Generalized Least squares (Regression) Estimator Variable Coefficient t-statistic p-value Size of Free Cash Flow 0.
All of these articles use an application of the generalized least squares (GLS) method first described by Parks (1967), a method designed to deal with some common problems that occur in TSCS data.
TABLE 3 Generalized Least Squares Estimates Country [[phi].
10 level, thereby providing evidence of heteroskedasticity relative to the weighting variable and indicating that the use of generalized least squares is appropriate.
We use two techniques to measure Andrew's impact on insurance stocks: a generalized least squares (GLS) estimation technique based on Zellner's (1962) seemingly unrelated regression model and the standard event study cumulative abnormal returns (CAR) tests adjusted for cross-sectional dependence.
The Parks method uses feasible generalized least squares (FGLS) for dealing with this error process.
We use generalized least squares to test the relationship between the number of patents issued to U.
Generalized least squares were used to obtain efficient estimates under the assumptions of cross-sectional heteroskedasticity and a common autoregressive process.
Through the use of a transformed generalized least squares regression model, allowance is made for: no-fault, population density, state-specific price-level, and automobile safety/fatality differences.
Once the model is defined, data from the National Science Foundation are incorporated so this process can be explored using a generalized least squares method.

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