simdat


A simulated dataset to illustrate multilevel modelling using I-priors.


datasets

In a linear regression setting, priors can be assigned to the regression function using a vector space framework, and the posterior estimate of the regression function obtained. I-priors are a class of such priors based on the principle of maximum entropy. While the main interest of I-prior modelling is prediction, inference is also possible, e.g. via log-likelihood ratio tests. This package supports both formula and non-formula based input. Estimation is mainly done via an EM algorithm, but there is flexibility in using any R optimiser to maximise the log-likelihood computed by the kernel loader function.

Haziq Jamil

iprior

Linear Regression using I-Priors

simdat function

A data frame with 53940 rows and 10 variables:
<dl> </dl>

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simdat: Random slopes model simulated data

Description

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Examples