public static void Test_herlall()
{
double[] time = { 2, 1, 2, 3, 2, 1 };
int[] num = { 0, 1, 1, 0, 2, 0 };
int[] type = { 0, 0, 0, 0, 0, 0 };
SRMData data = new SRMData();
data.SetData(time, num, type);
EMConf emconf = new EMConf();
emconf.Progress = 10000;
emconf.MaxIter = 1000000;
emconf.StopCond = StopCondition.PARAMETER; //.LLF;
HErlang.HErlangAll all = new HErlang.HErlangAll(5);
all.FitAll(data, emconf, null);
Console.WriteLine(all.GetModelName());
Console.WriteLine(all.GetParam().ToString());
Console.WriteLine();
Result result = all.Calc(data);
print_result(result);
}
public static void Test_srm()
{
double[] time = { 2, 1, 2, 3, 2, 1 };
int[] num = { 0, 1, 1, 0, 2, 0 };
int[] type = { 0, 0, 0, 0, 0, 0 };
SRMData data = new SRMData();
data.SetData(time, num, type);
SRM[] models = new SRM[11];
models[0] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.EXP);
models[1] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.GAMMA);
models[2] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.PARETO);
models[3] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.TNORM);
models[4] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.LNORM);
models[5] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.TLOGIS);
models[6] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.LLOGIS);
models[7] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.TXVMAX);
models[8] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.TXVMIN);
models[9] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.LXVMAX);
models[10] = SRMFactory.GetInstance().CreateSRM(OriginalSRMModel.LXVMIN);
EMConf[] emconf = new EMConf[11];
EM[] em = new EM[11];
for (int i = 0; i < 11; i++)
{
emconf[i] = new EMConf();
em[i] = new EM(models[i], emconf[i], new MODELS.SRMConsoleMessage(models[i], emconf[i]));
}
for (int i = 0; i < 11; i++)
{
emconf[i].Progress = 1;
emconf[i].StopCond = StopCondition.PARAMETER;
em[i].Initialize(data);
em[i].Fit(data);
Console.WriteLine(emconf[i].Status);
Result result = models[i].Calc(data);
print_result(result);
}
}
public static void Test_cphem()
{
double[] time = { 2, 1, 2, 3, 2, 1 };
int[] num = { 0, 1, 1, 0, 2, 0 };
int[] type = { 0, 0, 0, 0, 0, 0 };
SRMData data = new SRMData();
data.SetData(time, num, type);
int nm = 4;
SRM[] models = new SRM[nm];
models[0] = new CPH.CPHEMSRM(new CPH.CPHParam(1));
models[1] = new CPH.CPHEMSRM(new CPH.CPHParam(2));
models[2] = new CPH.CPHEMSRM(new CPH.CPHParam(3));
models[3] = new CPH.CPHEMSRM(new CPH.CPHParam(4));
EMConf[] emconf = new EMConf[nm];
EM[] em = new EM[nm];
for (int i = 0; i < nm; i++)
{
emconf[i] = new EMConf();
em[i] = new EM(models[i], emconf[i], new MODELS.SRMConsoleMessage(models[i], emconf[i]));
}
for (int i = 0; i < nm; i++)
{
emconf[i].Progress = 1;
emconf[i].StopCond = StopCondition.LLF;
em[i].Initialize(data);
em[i].Fit(data);
Console.WriteLine(emconf[i].Status);
Result result = models[i].Calc(data);
print_result(result);
}
}
public void Fit(SRMData data)
{
emparam.Status = Status.PROCESSING;
//if (emparam.initflag)
//{
// initialize(data);
//}
double prev_llf;
emparam.Llf = -double.MaxValue;
model.Pre_em(data);
emparam.Cnt = 0;
while (true)
{
prev_llf = emparam.Llf;
model.GetParam().CopyTo(prev_param);
emparam.Llf = model.Emstep(data);
if (emparam.Llf < prev_llf)
{
msg.Warning();
}
switch (emparam.StopCond)
{
case StopCondition.LLF:
emparam.Aerror = NMath.Abs(emparam.Llf - prev_llf);
emparam.Rerror = emparam.Aerror / NMath.Abs(prev_llf);
break;
case StopCondition.PARAMETER:
emparam.Aerror = model.GetParam().Adiff(prev_param);
emparam.Rerror = model.GetParam().Rdiff(prev_param);
break;
}
emparam.Cnt++;
if (double.IsNaN(emparam.Llf))
{
emparam.Status = Status.NUMERICALERROR;
break;
}
if (emparam.PrintFlag && emparam.Cnt % emparam.Progress == 0)
{
msg.Show();
}
if (emparam.Aerror < emparam.Atol && emparam.Rerror < emparam.Rtol)
{
emparam.Status = Status.CONVERGENCE;
break;
}
if (emparam.Cnt >= emparam.MaxIter)
{
emparam.Status = Status.MAXITERATION;
break;
}
}
msg.Final();
model.Post_em(data);
}
public void Initialize(SRMData data)
{
model.Initialize(data);
}
public override Result Calc(SRMData data)
{
Result result = new Result();
double te = data.TotalTime;
double me = data.TotalFaults;
int dsize = 0;
double[] t = new double[data.Size];
double[] x = new double[data.Size];
double[] w = new double[data.Size];
for (int i = 0; i < data.Size; i++)
{
if (data.Time[i] > 0)
{
t[dsize] = data.Time[i];
x[dsize] = data.Fault[i];
w[dsize] = data.Type[i];
dsize++;
}
else
{
w[dsize] += data.Fault[i];
w[dsize] += data.Type[i];
}
}
double ctime = 0.0;
double prevmvf = 0.0;
double cfault = 0.0;
double csum = 0.0;
double dsum = 0.0;
double llf = 0.0;
double cmvf = 0.0;
double pdf = 0.0;
double dmvf = 0.0;
for (int i = 0; i < dsize; i++)
{
ctime += t[i];
cfault += x[i];
cfault += w[i];
cmvf = Omega * dist.Cdf(ctime);
pdf = Omega * dist.Pdf(ctime);
dmvf = cmvf - prevmvf;
prevmvf = cmvf;
if (x[i] > 0)
{
llf += x[i] * NMath.Log(dmvf) - NMath.Lgamma(x[i] + 1);
}
if (w[i] > 0)
{
llf += w[i] * NMath.Log(pdf);
}
csum += (cmvf - cfault) * (cmvf - cfault);
dsum += (dmvf - (x[i] + w[i])) * (dmvf - (x[i] + w[i]));
}
llf += -cmvf;
result.Llf = llf;
result.Aic = -2 * result.Llf + 2 * NParam();
result.Bic = -2 * result.Llf + NParam() * NMath.Log(dsize);
result.CMse = csum / dsize;
result.CMsee = csum / (dsize - NParam());
result.DMse = dsum / dsize;
result.DMsee = dsum / (dsize - NParam());
result.Residual = Omega - cmvf;
result.Total = me + result.Residual;
result.Ffp = NMath.Exp(-result.Residual);
result.CMttf = te / cmvf;
result.IMttf = 1.0 / pdf;
result.Bexlife = Bexlife(te, cmvf / Omega, result.Ffp, 0.1);
result.Median = Bexlife(te, cmvf / Omega, result.Ffp, 0.5);
result.ConBexlife = ConBexlife(te, cmvf / Omega, result.Ffp, 0.1);
result.ConMedian = ConBexlife(te, cmvf / Omega, result.Ffp, 0.5);
MTTFValue mttf = new MTTFValue(Reliab, 1.0e-8);
result.ConMttf = mttf.Calc(te, cmvf, result.Ffp, ConBexlife(te, cmvf / Omega, result.Ffp, 1.0e-6));
return(result);
}
// public abstract void fit(Data.SRMFData data); public abstract Result Calc(SRMData data);
