scholarly journals Approximate moments of extremes

Author(s):  
Christopher S Withers ◽  
Saralees Nadarajah
Keyword(s):  
PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254811
Author(s):  
Sarah M. Kreidler ◽  
Brandy M. Ringham ◽  
Keith E. Muller ◽  
Deborah H. Glueck

We derive a noncentral F power approximation for the Kenward and Roger test. We use a method of moments approach to form an approximate distribution for the Kenward and Roger scaled Wald statistic, under the alternative. The result depends on the approximate moments of the unscaled Wald statistic. Via Monte Carlo simulation, we demonstrate that the new power approximation is accurate for cluster randomized trials and longitudinal study designs. The method retains accuracy for small sample sizes, even in the presence of missing data. We illustrate the method with a power calculation for an unbalanced group-randomized trial in oral cancer prevention.


1989 ◽  
Vol 31 (7) ◽  
pp. 875-883 ◽  
Author(s):  
Philip Holgate
Keyword(s):  

2016 ◽  
Vol 132 (2) ◽  
pp. 617-663 ◽  
Author(s):  
Anmol Bhandari ◽  
David Evans ◽  
Mikhail Golosov ◽  
Thomas J. Sargent

Abstract A Ramsey planner chooses a distorting tax on labor and manages a portfolio of securities in an economy with incomplete markets. We develop a method that uses second order approximations of Ramsey policies to obtain formulas for conditional and unconditional moments of government debt and taxes that include means and variances of the invariant distribution as well as speeds of mean reversion. The asymptotic mean of the planner's portfolio minimizes a measure of fiscal risk. We obtain analytic expressions that approximate moments of the invariant distribution and apply them to data on a primary government deficit, aggregate consumption, and returns on traded securities. For U.S. data, we find that the optimal target debt level is negative but close to zero, the invariant distribution of debt is very dispersed, and mean reversion is slow.


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