pin_confint: PIN confidence intervals

In pinbasic: Fast and Stable Estimation of the Probability of Informed Trading (PIN)

Description

Computes confidence intervals for the probability of informed trading by simulation

Usage

pin_confint(param = NULL, numbuys = NULL, numsells = NULL,
  method = "HAC", lower = rep(0, 5), upper = c(1, 1, rep(Inf, 3)),
  n = 10000, seed = NULL, level = 0.95, ncores = 1)

Arguments

param	numeric: (named) vector of model parameters (valid names: 'alpha', 'delta', 'epsilon_b', 'epsilon_s', 'mu'), length must equal 5
numbuys	numeric: vector of daily buys
numsells	numeric: vector of daily sells
method	character Switch between algorithms for generating initial values, valid choices are: 'Grid', 'HAC' and 'HAC_Ref'
lower	numeric: lower bounds for optimization, must have length of 5
upper	numeric: upper bounds for optimization, must have length of 5
n	integer: Number of simulation runs, defaults to 10000
seed	interpreted as integer or NULL: defaults to NULL, for more details see set.seed
level	numeric: Confidence level, defaults to 0.95
ncores	integer: Number of cpu cores utilized in computation, defaults to 1

Details

If names are not set for param or one or more of the vector names do not match the valid choices, they are internally set to 'alpha', 'delta', 'epsilon_b', 'epsilon_s', 'mu' (in this order).
By default, only one core is utilized in computations (ncores = 1). Confidence intervals can also be calculated in parallel, however, this only pays off for large values of n.

Value

numeric: confidence interval

pinbasic documentation built on May 2, 2019, 2:07 a.m.