sir.estimate
Class Options

java.lang.Object
  extended bysir.estimate.Options

public class Options
extends java.lang.Object

Title: Options object. Description: All about the configuration goes here Copyright: Company:

Version:
1.0 This class contains options for the SIREstimate program. Could have been implemented in the class itself, but this way it might be more flexible in case integration with the simulation part is done at some point.
Author:
Michael Höhle <hoehle@dina.kvl.dk>

Field Summary
static char diagTime
          Distribution of the Seroconversion period: 'E'=exponential, 'G'=gamma, 'N'=none (ignore)
static boolean expInfTime
          Is the infectious period exponentially distributed?
static boolean fixedSeed
          Are we using a random seed value or are we fixing the value to be able to get same results later on?
static boolean ignoreD
          Ignore any S specified, i.e. all D should be parametric?
static boolean ignoreE
          Ignore any E specified, i.e. all E should be parametric?
static boolean ignoreI
          Ignore any I specified, i.e. all I should be parametric?
static char incuTime
          Distribution type for incubation period
static double mcmc_betaNRWsigma
           
static double mcmc_betaRWsigma
          Std. dev of proposal distribution (Gaussian) when suggesting new beta values in the Metropolis Hastings setting.
static int mcmc_burnin
          Initial number of burnin samples to generate.
static double mcmc_deltaDRWsigma
          Std. dev of Gaussian proposal distribution for deltaD
static double mcmc_deltaERWsigma
          Std. dev of Gaussian proposal distribution for deltaE
static double mcmc_deltaIRWsigma
          Std. dev of Gaussian proposal distribution for deltaI
static double mcmc_ERWsigma
          Std. dev of Gaussian proposal distribution for E
static double mcmc_gammaDRWsigma
          Std. dev of Gaussian proposal distribution for gammaD
static double mcmc_gammaERWsigma
          Std. dev of Gaussian proposal distribution for gammaE
static double mcmc_gammaIRWsigma
          Std. dev of Gaussian proposal distribution for gammaI
static double mcmc_IRWsigma
          Std. dev of Gaussian proposal distribution for I
static double mcmc_RRWsigma
          Std. dev of Gaussian proposal distribution for R
static int mcmc_samples
          How many samples should the estimation be based on
static int mcmc_thin
          When generating samples, we only take each thin'th sample - others are thrown away
static boolean meanVar
          Should we use a mean/variance representation of all Gamma distribution?
static java.lang.String method
          Which method did we actually pick?
static int mml_mcsamples
          Number of samples to use in the Monte Carlo integration approximation of the marginal density
static int mml_samples
          How many different samples of \bm{I} is the estimation based on.
static double mml_sumscale
          Scale factor to use when adding the individual monte carlo samples.
static double mml_theta
          Cut off value for sampling
static boolean mml_verboseOptimizer
          Should the optimizer run silent or print extra information?
static boolean readFromFile
           
static int seed
          Seed value for the random generator (if required)
static boolean slowButSafe
          Internal option
 
Constructor Summary
Options()
           
 
Method Summary
 java.lang.String toString()
          Standard DEBUG routine.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
 

Field Detail

readFromFile

public static boolean readFromFile

fixedSeed

public static boolean fixedSeed
Are we using a random seed value or are we fixing the value to be able to get same results later on?


seed

public static int seed
Seed value for the random generator (if required)


ignoreE

public static boolean ignoreE
Ignore any E specified, i.e. all E should be parametric?


ignoreI

public static boolean ignoreI
Ignore any I specified, i.e. all I should be parametric?


ignoreD

public static boolean ignoreD
Ignore any S specified, i.e. all D should be parametric?


meanVar

public static boolean meanVar
Should we use a mean/variance representation of all Gamma distribution?


incuTime

public static char incuTime
Distribution type for incubation period


expInfTime

public static boolean expInfTime
Is the infectious period exponentially distributed? Note: meanVar=T not allowed if true


diagTime

public static char diagTime
Distribution of the Seroconversion period: 'E'=exponential, 'G'=gamma, 'N'=none (ignore)


method

public static java.lang.String method
Which method did we actually pick? Neater solution would be to have an interface and MCMC, ML, MML as classes each implementing their own run method.


slowButSafe

public static boolean slowButSafe
Internal option


mcmc_samples

public static int mcmc_samples
How many samples should the estimation be based on


mcmc_thin

public static int mcmc_thin
When generating samples, we only take each thin'th sample - others are thrown away


mcmc_burnin

public static int mcmc_burnin
Initial number of burnin samples to generate. Note: No thinning is applied here!


mcmc_betaRWsigma

public static double mcmc_betaRWsigma
Std. dev of proposal distribution (Gaussian) when suggesting new beta values in the Metropolis Hastings setting.


mcmc_betaNRWsigma

public static double mcmc_betaNRWsigma

mcmc_gammaERWsigma

public static double mcmc_gammaERWsigma
Std. dev of Gaussian proposal distribution for gammaE


mcmc_deltaERWsigma

public static double mcmc_deltaERWsigma
Std. dev of Gaussian proposal distribution for deltaE


mcmc_gammaIRWsigma

public static double mcmc_gammaIRWsigma
Std. dev of Gaussian proposal distribution for gammaI


mcmc_deltaIRWsigma

public static double mcmc_deltaIRWsigma
Std. dev of Gaussian proposal distribution for deltaI


mcmc_gammaDRWsigma

public static double mcmc_gammaDRWsigma
Std. dev of Gaussian proposal distribution for gammaD


mcmc_deltaDRWsigma

public static double mcmc_deltaDRWsigma
Std. dev of Gaussian proposal distribution for deltaD


mcmc_RRWsigma

public static double mcmc_RRWsigma
Std. dev of Gaussian proposal distribution for R


mcmc_IRWsigma

public static double mcmc_IRWsigma
Std. dev of Gaussian proposal distribution for I


mcmc_ERWsigma

public static double mcmc_ERWsigma
Std. dev of Gaussian proposal distribution for E


mml_samples

public static int mml_samples
How many different samples of \bm{I} is the estimation based on. Typically one is sufficient, but to check for stability of the MC Integration try a moderate number.


mml_mcsamples

public static int mml_mcsamples
Number of samples to use in the Monte Carlo integration approximation of the marginal density


mml_theta

public static double mml_theta
Cut off value for sampling


mml_verboseOptimizer

public static boolean mml_verboseOptimizer
Should the optimizer run silent or print extra information?


mml_sumscale

public static double mml_sumscale
Scale factor to use when adding the individual monte carlo samples. Use scaleFactor>1 to get an effect!

Constructor Detail

Options

public Options()
Method Detail

toString

public java.lang.String toString()
Standard DEBUG routine. Note: Not all parameters are shown.