View source: R/PosteriorModeNPP.R
ModeDeltaNormalNPP | R Documentation |
The function returns the posterior mode of the power parameter \delta
in multinomial population.
It calculates the log of the posterior density (up to a normalizing constant), and conduct a grid search
to find the approximate mode.
ModeDeltaNormalNPP(Data.Cur, Data.Hist,
CompStat = list(n0 = NULL, mean0 = NULL, var0 = NULL,
n1 = NULL, mean1 = NULL, var1 = NULL),
npoints = 1000,
prior = list(a = 1.5, delta.alpha = 1, delta.beta = 1))
Data.Cur |
a vector of individual level current data. |
Data.Hist |
a vector of individual level historical data. |
CompStat |
a list of six elements(scalar) that represents the
"compatibility(sufficient) statistics" for model parameters.
Default is
|
npoints |
is a non-negative integer scalar indicating number of points on a regular spaced grid between [0, 1], where we calculate the log of the posterior and search for the mode. |
prior |
a list of the hyperparameters in the prior for both
|
See example.
A numeric value between 0 and 1.
Zifei Han hanzifei1@gmail.com
Ibrahim, J.G., Chen, M.-H., Gwon, Y. and Chen, F. (2015). The Power Prior: Theory and Applications. Statistics in Medicine 34:3724-3749.
Duan, Y., Ye, K. and Smith, E.P. (2006). Evaluating Water Quality: Using Power Priors to Incorporate Historical Information. Environmetrics 17:95-106.
Berger, J.O. and Bernardo, J.M. (1992). On the development of reference priors. Bayesian Statistics 4: Proceedings of the Fourth Valencia International Meeting, Bernardo, J.M, Berger, J.O., Dawid, A.P. and Smith, A.F.M. eds., 35-60, Clarendon Press:Oxford.
Jeffreys, H. (1946). An Invariant Form for the Prior Probability in Estimation Problems. Proceedings of the Royal Statistical Society of London, Series A 186:453-461.
ModeDeltaBerNPP
;
ModeDeltaMultinomialNPP
;
ModeDeltaPoisNPP
ModeDeltaNormalNPP(CompStat = list(n0 = 50, mean0 = 0, var0 = 1,
n1 = 50, mean1 = 0, var1 = 1), npoints = 1000,
prior = list(a = 1.5, delta.alpha = 1, delta.beta = 1))
ModeDeltaNormalNPP(CompStat = list(n0 = 50, mean0 = 0, var0 = 1,
n1 = 40, mean1 = 0.2, var1 = 1), npoints = 1000,
prior = list(a = 1.5, delta.alpha = 1, delta.beta = 1))
ModeDeltaNormalNPP(CompStat = list(n0 = 50, mean0 = 0, var0 = 1,
n1 = 40, mean1 = 0.6, var1 = 1), npoints = 1000,
prior = list(a = 1.5, delta.alpha = 1, delta.beta = 1))
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