{"name":"zapweak","title":"Zap weak competitors","pagetitle":"Zap weak competitors — zapweak","aliases":"zapweak","author":"Robin K. S. Hankin","keywords":[],"description":"

Given a hyper2 object, discard competitors with a small estimated\nstrength.

","usage":"zapweak(H, minstrength = 1e-05, maxit, ...)","arguments":[{"name":"H","description":"

Object of class hyper2

"},{"name":"minstrength","description":"

Strength below which to discard competitors

"},{"name":"maxit","description":"

Maximum number of iterations; if missing, use\n size(H)-1

"},{"name":"…","description":"

Further arguments, passed to maxp()

"}],"has_args":true,"examples":"# NOT RUN {\n zapweak(icons) # removes noone\n# }\n# NOT RUN {\n#Takes too long\n zapweak(rowing) # removes everyone...\n# }\n","sections":[],"details":"

Iteratively discards the weakest player (if the estimated strength is\nless than minstrength) using discard_flawed().\nmaxp(..,n=1) for efficiency.

","value":"

Returns a slimmed-down hyper2 object with weak players\n removed.

","note":["","

This function is experimental and appears to be overly aggressive.\n For some likelihood functions zapweak() removes all the\n players.

I now think that there is no consistent way to remove weaker players\n from a likelihood function. I think the only way to do it is to look\n at the dataset that generates the likelihood function, somehow weed\n out the players with the poorest performance, and generate a new\n likelihood function without them.

"],"seealso":"

discard_flawed,maxp

","package":{"package":"hyper2","version":"2.0-1"}}

Description

Usage

Arguments

Value

Details

See Also

Examples