This function will run applyStrategy() on portfolio.st, once for each parameter combination as specified by the parameter distributions and constraints in the paramset. Results are gathered and returned as a list containing a slot for each parameter combination.
apply.paramset(strategy.st, paramset.label, portfolio.st, ..., account.st,
mktdata = NULL, nsamples = 0, user.func = NULL, user.args = NULL,
calc = "slave", audit = NULL, packages = NULL, verbose = FALSE,
paramsets, rule.subset = NULL, store = TRUE)the name of the strategy object
a label uniquely identifying the paramset within the strategy
the name of the portfolio
any other passthru parameters
the name of the account
optional xts mktdata object, will be passed unchanged to applyStrategy
if > 0 then take a sample of only size nsamples from the paramset
an optional user-supplied function to be run for each param.combo at the end, either on the slave or on the master (see calc)
user-supplied list of arguments for user.func
'slave' to run updatePortfolio() and tradesStats() on the slave and return all portfolios and orderbooks as a list: higher parallelization but more data transfer between master and slave; 'master' to have updatePortf() and tradeStats() run at the master and return all portfolios and orderbooks in the .blotter and .strategy environments resp: less parallelization but also less data transfer between slave and master; default is 'slave'
a user-specified environment to store a copy of all portfolios, orderbooks and other data from the tests, or NULL to trash this information
a vector specifying names of R packages to be loaded by the slave, default NULL
return full information, in particular the .blotter environment, default FALSE
a user-sepcified (sub)set of paramsets to run
ISO-8601 subset for period to execute rules over, default NULL
indicates whether to store the strategy in the .strategy environment
apply.paramset uses the foreach package to start the runs for each parameter combination, and as such allows for parallel processing. It is up to the caller to load and register an appropriate backend, eg. doMC, doParallel or doRedis.
add.distribution.constraint,
add.distribution.constraint,
delete.paramset