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Compute \(G(w,z)\) and its complement \(Q(w,z)=1-G(w,z)\) for a density-independent (drifted Wiener) model, on both linear and log scales.

Usage

ext_prob_di(w, z)

log_ext_prob_di(w, z)

log_ext_comp_di(w, z)

ext_prob_format_di(w, z, digits = 5L)

Arguments

w

Numeric; transformed parameter \(w=(\mu t+x_d)/(\sigma\sqrt{t})\).

z

Numeric; transformed parameter \(z=(-\mu t+x_d)/(\sigma\sqrt{t})\).

digits

Integer; significant digits for formatting (only for ext_prob_format_di).

Value

For ext_prob_di: numeric scalar \(G(w,z)\).
For log_ext_prob_di: numeric scalar \(\log G(w,z)\).
For log_ext_comp_di: numeric scalar \(\log Q(w,z)\).
For ext_prob_format_di: character string formatted for display.

Details

For any \(t>0\) with \(w+z>0\), $$ \Pr[T \leq t] = G(w,z)=\Phi(-w)+ \exp\!\left(\tfrac{z^2-w^2}{2}\right)\Phi(-z), \qquad Q(w,z)=1-G(w,z). $$ Here \(\Phi\) and \(\phi\) denote the standard normal CDF and PDF.

Stability strategy. (i) For large \(z\), rewrite the product \(\exp((z^2-w^2)/2)\,\Phi(-z)\) via the Mills ratio and replace it by an 8-term asymptotic series when \(z \ge 19\). (ii) On the log scale, use log-sum-exp and a stable log-difference (log1mexp) built from log1p/expm1 to retain tail info.

Domain. Scalar inputs are assumed and require \(w+z>0\).

Functions.

  • ext_prob_di(w,z): returns \(G(w,z)\) (linear scale).

  • log_ext_prob_di(w,z): returns \(\log G(w,z)\).

  • log_ext_comp_di(w,z): returns \(\log Q(w,z)\).

  • ext_prob_format_di(w,z,digits): formats a point estimate using repr_mode() and format_by_mode().

Author

Hiroshi Hakoyama, hiroshi.hakoyama@gmail.com