Wald's SPRT algorithm

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• Subject: [mg129801] Wald's SPRT algorithm
• From: richardgreco at gmail.com
• Date: Fri, 15 Feb 2013 01:56:48 -0500 (EST)
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```Has anyone worked with Sequential Probability Ratio Test (SPRT) in Mathematica.

I have this SPRT which looks at a BernoulliDistribution[] (see below) for successes out of trials.

My application is comparing means of two distributions and to determine if I should accept or reject a hypothesis.

I am having a hard time working out it out for my application, a PoissonDistribution and comparing the means.  What I am looking to do is, if I keep taking data every minute from a sensor (sensor reading 120 cpm for exmaple), I want to be able to know if it is over a threshold or is it background using SPRT.

Here is the notebook for the Bernoulli process using BernoulliDistributions.  I started with this article: "The Sequential Probability Ratio Test" Phil, Robert L. (1998)

Null;
alpha = .05;
beta = .05;
p0 = .8;
p1 = .98;
k0 = alpha/(1 - beta);
k1 = (1 - alpha)/beta;
c0 = Log[k0];
c1 = Log[k1];
plt1 = Plot[{c0, c1}, {x, 0, 20}, PlotRange -> {1.7 c0, 1.7*c1},
DisplayFunction -> Identity];
f0[x_] := PDF[BernoulliDistribution[p0], x]
f1[x_] := PDF[BernoulliDistribution[p1], x]
LLR[x_] := Log[f0[x]/f1[x]]
Truep = .95;
sum = 0;
stopflag = 0;
decflag = .5;
n = 0;
printflag = 1;
sumData = {};
Print["n", "  ", "samplepoint", " ", "LLR[samplepoint]", "    ", \
"sum", "    ", "stopflag", " ", "decflag"]
While[stopflag == 0, n = n + 1;
samplepoint = Random[BernoulliDistribution[Truep]];
sum = sum + LLR[samplepoint]; AppendTo[sumData, {n, sum}];
If[sum < c0, stopflag = 1; decflag = 1;,
If[sum > c1, stopflag = 1; decflag = 0;, Null];];
If[printflag > 0,
Print[n, " ", samplepoint, " ", LLR[samplepoint], " ", sum, " ",
stopflag, " ", decflag], Null]]
plt2 = ListPlot[sumData, PlotStyle -> {PointerSize[.015]},
DisplayFunction :> Identity];
Show[{plt1, plt2}, DisplayFunction -> \$DisplayFunction]

```

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