Maximum Likelihood Problem

*To*: mathgroup at smc.vnet.net*Subject*: [mg46428] Maximum Likelihood Problem*From*: sabrinacasagrande at hotmail.com (sabbri)*Date*: Tue, 17 Feb 2004 07:46:46 -0500 (EST)*Sender*: owner-wri-mathgroup at wolfram.com

I need to generate an algorithm in order to estimate the parameters of an equation . It's probably a mistake in my codes that prevents me to get the right results. DATA (Sample Path generating): I generated the data using an approximation of the differential equation dXt = - B Xt dt + s dWt: u[x_]:= x + m[x]*t + s[x]* ((t)^(1/2))*(Quantile[NormalDistribution[0,1],Random[]]) where I state m[x_]= -10 x, and s[x_]= 1, t=1/12 Then I generate the data with Table[NestList[u,0.2,100],{1}]]. So I have my data with the true parameters value, B=10 and s=1. ALGORITHM: I use an approximation (of the transition density probability function). I constructed the approximation based on the saddle points method (or Laplace Method). sigx[x_] := s mx[x_] := -B x g[x_] = Integrate[(1/sigx[u]), {u, 0, x}] sigy[x_] = 1 my[x_] = (mx[x]/sigx[x]) - (D[sigx[x], x]/2) fi[z_] = (1/Sqrt[2 Pi]) (Exp[-(z^2)/2]) lamy[x_] = (-1/2) (((my[x])^2) + D[my[x], x]) c[y_, x_, j_] := c[y, x, j] = ((j)*(y - x)^(-j)) (Integrate[((w - x)^(j - 1))((lamy[w]c[w, x, j - 1]) + ((D[c[w, x, j - 1], {w, 2}])(1/2))), {w, x,y}]) c[y_, x_, 0] = 1 py[t_, y_, x_] = (1/Sqrt[t]) (fi[(y - x)/(Sqrt[t])]) (Exp[Integrate[my[w], {w, x,y}]]) (Sum[c[y, x, k] ((t)^k)/(k!), {k, 0, 1}]) px[t_, y_, x_] = (py[t, g[y], g[x]]/sigx[g[x]]) And finally I get a function (the likelihood function) L[N_] = Sum[Log[px[t, x[n + 1], x[n]]], {n, 1, N}]/N where x[n_] are the values I generated above. So x[n_]:= Extract[data,{1,n}] Now I try to maximize it. I tried using two methods: 1)the function Maximize Maximize[{L[99],s>0},{B,s}] 2) Solve[] on the derivatives == 0 of my target function. Solve[{D[L[99],B]==0,D[L[99],s]==0},{B,s}] In none of this case I can get the results. (Mind that I generated the data attributing the values to parameters, so data were generated with the right values: I should obtain those values while maximizing!!!) Can you help me? Where am I wrong?