Patterns in static

Apophenia

Data Fields
apop_arms_settings Struct Reference

Data Fields

double * xinit
 
double xl
 
double xr
 
double convex
 
int ninit
 
int npoint
 
char do_metro
 
double xprev
 
int neval
 
arms_state * state
 
apop_modelmodel
 

Detailed Description

to perform derivative-free adaptive rejection sampling with metropolis step

Field Documentation

double apop_arms_settings::convex

Adjustment for convexity

char apop_arms_settings::do_metro

Whether metropolis step is required. (I.e., set to one if you're not sure if the function is log-concave). Set to 'y'es or 'n'o

apop_model* apop_arms_settings::model

The model from which I will draw. Mandatory. Must have either a log_likelihood or p method.

int apop_arms_settings::neval

On exit, the number of function evaluations performed

int apop_arms_settings::ninit

Number of starting values supplied (i.e. number of elements in xinit)

int apop_arms_settings::npoint

Maximum number of envelope points. I malloc space for this many doubles at the outset. Default = 1e5.

double* apop_arms_settings::xinit

A double* giving starting values for x in ascending order. Default: -1, 0, 1. If this isn't NULL, I need at least three items.

double apop_arms_settings::xl

Left bound. If you don't give me one, I'll use min[min(xinit)/10, min(xinit)*10].

double apop_arms_settings::xprev

Previous value from Markov chain

double apop_arms_settings::xr

Right bound. If you don't give me one, I'll use max[max(xinit)/10, max(xinit)*10].

Autogenerated by doxygen on Sun Oct 26 2014 (Debian 0.999b+ds3-2).