📄 tryrand3.cpp
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static Real SortThreeDescending(Real* a, Real* b, Real* c);static void MyQuickSortAscending(Real* first, Real* last, int depth);static void InsertionSortAscending(Real* first, const int length, int guard);static Real SortThreeDescending(Real* a, Real* b, Real* c){ // sort *a, *b, *c; return *b; optimise for already sorted if (*a >= *b) { if (*b >= *c) return *b; else if (*a >= *c) { Real x = *c; *c = *b; *b = x; return x; } else { Real x = *a; *a = *c; *c = *b; *b = x; return x; } } else if (*c >= *b) { Real x = *c; *c = *a; *a = x; return *b; } else if (*a >= *c) { Real x = *a; *a = *b; *b = x; return x; } else { Real x = *c; *c = *a; *a = *b; *b = x; return x; }}void SortAscending(Real* data, int max){ if (max > DoSimpleSort) MyQuickSortAscending(data, data + max - 1, 0); InsertionSortAscending(data, max, DoSimpleSort);}static void InsertionSortAscending(Real* first, const int length, int guard)// guard gives the length of the sequence to scan to find first// element (eg guard = length){ if (length <= 1) return; // scan for first element Real* f = first; Real v = *f; Real* h = f; if (guard > length) guard = length; int i = guard - 1; while (i--) if (v > *(++f)) { v = *f; h = f; } *h = *first; *first = v; // do the sort i = length - 1; f = first; while (i--) { Real* g = f++; h = f; v = *h; while (*g > v) *h-- = *g--; *h = v; }}static void MyQuickSortAscending(Real* first, Real* last, int depth){ for (;;) { const int length = last - first + 1; if (length < DoSimpleSort) return; if (depth++ > MaxDepth) Throw(Exception("QuickSortAscending fails")); Real* centre = first + length/2; const Real test = SortThreeDescending(last, centre, first); Real* f = first; Real* l = last; for (;;) { while (*(++f) < test) {} while (*(--l) > test) {} if (l <= f) break; const Real temp = *f; *f = *l; *l = temp; } if (f > centre) { MyQuickSortAscending(l+1, last, depth); last = f-1; } else { MyQuickSortAscending(first, f-1, depth); first = l+1; } }}Real NormalDF(Real x){ // from Abramowitz and Stegun - accuracy 7.5E-8 // accuracy is absolute; not relative // eventually will need a better method // but good enough here Real t = 1.0 / (1.0 + 0.2316419 * fabs(x)); t = ( 0.319381530 + (-0.356563782 + ( 1.781477937 + (-1.821255978 + 1.330274429 * t) * t) * t) * t) * t; t = 0.3989422804014326779399461 * exp(-0.5 * x * x) * t; return (x < 0) ? t : 1.0 - t;}void ChiSquaredTest(int* Observed, Real* Prob, int N, int n){ // go for at least two expected observations per cell // work in from ends if (N <= 0) { cout << "no categories" << endl; return; } if (n <= 0) { cout << "no data" << endl; return; } int O1 = 0; Real E1 = 0.0; int O2 = 0; Real E2 = 0.0; Real CS = 0.0; int df = 0; int i = 0; int Ni = N; Real ToGo = n; for (;;) { O1 += Observed[i]; Real e1 = n * Prob[i]; E1 += e1; ToGo -= e1; if (E1 >= 2.0 && ToGo + E2 >= 2.0) { CS += square(O1 - E1) / E1; df += 1; O1 = 0; E1 = 0.0; } if (i == Ni) break; ++i; O2 += Observed[Ni]; Real e2 = n * Prob[Ni]; E2 += e2; ToGo -= e2; if (E2 >= 2.0 && ToGo + E1 >= 2.0) { CS += square(O2 - E2) / E2; df += 1; O2 = 0; E2 = 0.0; } if (i == Ni) break; --Ni; } E1 += E2; O1 += O2; if (E1 > 0.0) { CS += square(O1 - E1) / E1; df += 1; } if (fabs(ToGo) >= 0.01) cout << "chi-squared program fails - "; cout << "chisq = " << CS << "; df = " << (df-1) << "; 95% pt. = " << invchi95(df-1) << "; 99% pt. = " << invchi99(df-1) << endl;}void TestBinomial(int N, Real p, int n){ Binomial X(N, p); Real q = 1.0 - p; Real ln_p = log(p); Real ln_q = log(q); int* obs = new int [N+1]; if (!obs) Throw(Bad_alloc()); Real* prob = new Real [N+1]; if (!prob) Throw(Bad_alloc()); int i; for (i = 0; i <= N; i++) { obs[i] = 0; prob[i] = exp(ln_gamma(N+1) - ln_gamma(i+1) - ln_gamma(N-i+1) + i * ln_p + (N-i) * ln_q); } for (i = 0; i < n; i++) { int b = (int)X.Next(); if (b < 0 || b > N) Throw(Logic_error("Binomial error")); obs[b]++; } cout << "Binomial: "; ChiSquaredTest(obs, prob, N, n); delete [] obs; delete [] prob;}void TestPoisson(Real mu, int n){ Poisson X(mu); Real ln_mu = log(mu); int N = (int)(20 + mu + 10 * sqrt(mu)); // set upper bound if (N > n) { cout << "Poisson: range too large" << endl; return; } int* obs = new int [N+1]; if (!obs) Throw(Bad_alloc()); Real* prob = new Real [N+1]; if (!prob) Throw(Bad_alloc()); int i; for (i = 0; i <= N; i++) { obs[i] = 0; prob[i] = exp(i * ln_mu - mu - ln_gamma(i+1)); } for (i = 0; i < n; i++) { int b = (int)(X.Next()); if (b < 0 || b > N) Throw(Logic_error("Poisson error")); obs[b]++; } cout << "Poisson: "; ChiSquaredTest(obs, prob, N, n); delete [] obs; delete [] prob;}void TestNegativeBinomial(Real NX, Real P, int n){ NegativeBinomial X(NX, P); Real Q = 1.0 + P; Real p = 1.0 / Q; Real q = 1.0 - p; Real ln_p = log(p); Real ln_q = log(q); Real mean = NX * P; Real var = mean * Q; int N = (int)(20 + mean + 100 * sqrt(var)); // set upper bound // won't be good enough for large P if (N > n) { cout << "NegativeBinomial: range too large" << endl; return; } int* obs = new int [N+1]; if (!obs) Throw(Bad_alloc()); Real* prob = new Real [N+1]; if (!prob) Throw(Bad_alloc()); int i; for (i = 0; i <= N; i++) { obs[i] = 0; prob[i] = exp(ln_gamma(NX+i) - ln_gamma(i+1) - ln_gamma(NX) + NX * ln_p + i * ln_q); } for (i = 0; i < n; i++) { int b = (int)X.Next(); if (b < 0 || b > N) Throw(Logic_error("NegativeBinomial error")); obs[b]++; } cout << "NegativeBinomial: "; ChiSquaredTest(obs, prob, N, n); delete [] obs; delete [] prob;}void TestDiscreteGen(int N, Real* prob, int n){ DiscreteGen X(N, prob); int* obs = new int [N]; if (!obs) Throw(Bad_alloc()); int i; for (i = 0; i < N; i++) obs[i] = 0; for (i = 0; i < n; i++) { int b = (int)X.Next(); if (b < 0 || b >= N) Throw(Logic_error("DiscreteGen error")); obs[b]++; } cout << "DiscreteGen: "; ChiSquaredTest(obs, prob, N-1, n); delete [] obs;}// Calculate 95% point of chi-squared distributiondouble invchi95(int N)// upper 95% point of chi-squared distribution{ if (N < 0) Throw(Logic_error("Error in invchi95 arg")); if (N < 30) { double Q[] = { 0, 3.841459, 5.991465, 7.814728, 9.487729, 11.0705, 12.59159, 14.06714, 15.50731, 16.91898, 18.30704, 19.67506, 21.02601, 22.36199, 23.68475, 24.99576, 26.2962, 27.58709, 28.86928, 30.14351, 31.4104, 32.6705, 33.9244, 35.1725, 36.4151, 37.6525, 38.8852, 40.1133, 41.3372, 42.5569 }; return Q[N]; } else { double A = 1.0/(4.5 * N); double H = (-0.0002 * 60)/N; double Q = N * cube(1 - A + (1.645 - H) * sqrt(A)); return Q; }}// Calculate 99% point of chi-squared distributiondouble invchi99(int N)// upper 99% point of chi-squared distribution{ if (N < 0) Throw(Logic_error("Error in invchi99 arg")); if (N < 30) { double Q[] = { 0, 6.63490, 9.21034, 11.3449, 13.2767, 15.0863, 16.8119, 18.4753, 20.0902, 21.6660, 23.2093, 24.7250, 26.2170, 27.6883, 29.1413, 30.5779, 31.9999, 33.4087, 34.8053, 36.1908, 37.5662, 38.9321, 40.2894, 41.6384, 42.9798, 44.3141, 45.6417, 46.9630, 48.2782, 49.5879 }; return Q[N]; } else { double A = 1.0/(4.5 * N); double H = (0.0008 * 60)/N; double Q = N * cube(1 - A + (2.326 - H) * sqrt(A)); return Q; }}
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