convertDeltaToExpParams: converted input deltas to parameters for exponential baselines

Description

For each exponential baseline family, convert delta range into corresponding lambdas and weights.

Usage

convertDeltaToExpParams(
  family,
  alternative,
  threshold,
  m_pre,
  delta_lower,
  delta_upper,
  k_max
)

Value

A list of weights and lambdas

Arguments

family

Distribution of underlying univariate observations.

Normal: (sub-)Gaussian with sigma = 1.
Ber: Bernoulli distribution on {0,1}.
Bounded: General bounded distribution on [0,1]

alternative

Alternative / post-change mean space

two.sided: Two-sided test / change detection
greater: Alternative /post-change mean is greater than null / pre-change one
less: Alternative /post-change mean is less than null / pre-change one

threshold

Stopping threshold. We recommend to use log(1/alpha) for "ST" and "SR" methods where alpha is a testing level or 1/ARL. for "CU" and "GRLCU", we recommend to tune the threshold by using domain-specific sampler to hit the target ARL.

m_pre

The boundary of mean parameter in null / pre-change space

delta_lower

Minimum gap between null / pre-change space and alternative / post-change one. It must be strictly positive for ST, SR and CU. Currently, GLRCU does not support the minimum gap, and this param will be ignored.

delta_upper

Maximum gap between null / pre-change space and alternative / post-change one. It must be strictly positive for ST, SR and CU. Currently, GLRCU does not support the maximum gap, and this param will be ignored.

k_max

Positive integer to determine the maximum number of baselines. For GLRCU method, it is used as the lookup window size for GLRCU statistics.