lib-r-math.js - npm Package Compare versions

Comparing version 1.0.13 to 1.0.14

lib/_general.ts

@@ -0,1 +1,49 @@
+// find more constants of the kind M_XX_XX here
+// https://svn.r-project.org/R/trunk/src/include/Rmath.h0.in
+
+
+/*
+
+  WHY DO WE USE CUSTOM ROUND INSTEAD OF Javascript "Math.round" ?
+  
+  https://developer.mozilla.org/en/docs/Web/JavaScript/Reference/Global_Objects/Math/round
+
+  Note that this differs from many languages' round() functions, which often round this case to the next integer away from zero, instead (giving a different result in the case of negative numbers with a fractional part of exactly 0.5).
+
+*/
+
+
+
+export const sqr = (x: number) => x * x;
+export const ceil = Math.ceil;
+export const trunc = Math.trunc;
+export const log10 = Math.log10;
+export const LONG_MAX = Number.MAX_SAFE_INTEGER;
+export const DBL_MAX_10_EXP = Math.log10(Number.MAX_VALUE);
+export const MAX_DIGITS = DBL_MAX_10_EXP;
+export const INT_MAX = Number.MAX_SAFE_INTEGER;
+export const INT_MIN = Number.MIN_SAFE_INTEGER;
+
+export function rround(x: number) {
+
+    if (x < 0) {
+        return trunc(x - 0.5);
+    }
+    return trunc(x + 0.5);
+}
+
+
+/* 
+    nearbyint is C99, so all platforms should have it (and AFAIK, all do) 
+*/
+export const DBL_MANT_DIG = 18;
+export const FLT_MANT_DIG = DBL_MANT_DIG;
+export const M_LN2 = 0.693147180559945309417232121458;	/* ln(2) */
+export const M_1_SQRT_2PI = 0.398942280401432677939946059934;
+export const nearbyint = rround;
+export const R_forceint = nearbyint;
+export const R_rint = nearbyint;
+
+export const M_2PI = 6.283185307179586476925286766559;
+export const M_LN_2PI = 1.837877066409345483560659472811;
 export const sqrt = Math.sqrt;
@@ -6,13 +54,10 @@ export const DBL_EPSILON = 1E-16; //true for javascript, this was tested
 export const exp = Math.exp;
-export const rtnsig_BESS = 1e-4;
-export const enten_BESS = 1e308;
-export const xlrg_BESS_IJ = 1e5;
-export const enmten_BESS = 8.9e-308;
+
+export const isInteger = Number.isInteger;
 export const sin = Math.sin;
 export const cos = Math.cos;
 export const pow = Math.pow;
-export const ensig_BESS = 1e16;
+
 export const M_1_PI = 1.0 / Math.PI;
-export const sqxmin_BESS_K = 1.49e-154;
-export const xmax_BESS_K = 705.342;/* maximal x for UNscaled answer */
+
 export const R_FINITE = (x: number) => Number.isFinite(x);
@@ -22,8 +67,8 @@ export const NaN = Number.NaN;
 export const DBL_MIN = FLT_MIN;
-export const xlrg_BESS_Y = 1e8;
+
 export const log = Math.log;
 export const ISNAN = Number.isNaN;
-export const thresh_BESS_Y = 16.;
-export const M_eps_sinc = 2.149e-8;
+
 export const ML_NAN = NaN;
+export const round = Math.round;
 export const ML_POSINF = Number.POSITIVE_INFINITY;
@@ -33,9 +78,45 @@ export const ML_NEGINF = Number.NEGATIVE_INFINITY;
 export const M_PI_2 = Math.PI / 2;
+export const M_LN_SQRT_PI = 0.5723649429247; // log(sqrt(pi)) 
 export const M_LN_SQRT_2PI = 0.918938533204672741780329736406; // log(sqrt(2*pi)) 
 export const M_LN_SQRT_PId2 = 0.225791352644727432363097614947;	// log(sqrt(pi/2)) 
-export const R_D__0 = (log: boolean) => { return log ? ML_NEGINF : 0.0; };
+
+export const R_D__1 = (log_p: boolean) => {
+    return log_p ? 0. : 1.0;
+};
+
+export const R_D__0 = (log: boolean): number => {
+    return log ? ML_NEGINF : 0.0;
+};
+
+
+
+export function R_P_bounds_01(lower_tail: boolean, log_p: boolean, x: number, x_min: number, x_max: number): number | undefined {
+    if (x <= x_min) return R_DT_0(lower_tail,  log_p);
+    if (x >= x_max) return R_DT_1(lower_tail,  log_p);
+    return undefined;
+}
+
+export const R_DT_0 = (lower_tail: boolean,log_p: boolean): number => {
+    return lower_tail ? R_D__0(log_p) : R_D__1(log_p);
+};
+export const R_DT_1 = (lower_tail: boolean, log_p: boolean): number => {
+    return lower_tail ? R_D__1(log_p) : R_D__0(log_p);
+};
+export const R_D_val = (log_p: boolean, x: number) => {
+    return (log_p ? log(x) : (x));
+};
+
+
+export const R_D_exp = (log_p: boolean, x: number): number => {
+
+    return (log_p ? (x) : exp(x));
+    /* exp(x) */
+}
+
 export const floor = Math.floor;
-export const trunc = Math.trunc;
+
 export const M_SQRT_2dPI = 0.797884560802865355879892119869; // sqrt(2/pi) 
-export const R_D_exp = (x: any, logP: any) => { return !!logP ? (x) : Math.exp(x); }; /* exp(x) */
+
+export const M_LOG10_2 = 0.301029995663981195213738894724;
+
 export enum ME {
@@ -94,5 +175,13 @@ ME_NONE = 0, // no error
     return ML_NAN;
+}
 
+export function R_D_nonint_check(log: boolean, x: number) {
+    if (R_nonint(x)) {
+        MATHLIB_WARNING('non-integer x = %f', x);
+        return R_D__0(log);
+    }
+    return undefined;
 }
 
+
 export function fabs(x: number) {
@@ -106,3 +195,3 @@ return (x < 0 ? -x : x);
 
-export function fmax2(x: number, y: number) {
+export function fmax2(x: number, y: number): number {
     if (ISNAN(x) || ISNAN(y)) {
@@ -112,2 +201,247 @@ return x + y;
     return (x < y) ? y : x;
-}
+}
+
+export function fmin2(x: number, y: number): number {
+    if (ISNAN(x) || ISNAN(y)) {
+        return x + y;
+    }
+    return (x < y) ? x : y;
+}
+
+export function isOdd(k: number) {
+    return (floor(k) % 2) === 1;
+}
+
+
+export function Rf_d1mach(i: number): number {
+
+    switch (i) {
+        case 1: return DBL_MIN;
+        case 2: return DBL_MAX;
+
+        case 3: /* = FLT_RADIX  ^ - DBL_MANT_DIG
+          for IEEE:  = 2^-53 = 1.110223e-16 = .5*DBL_EPSILON */
+            return 0.5 * DBL_EPSILON;
+
+        case 4: /* = FLT_RADIX  ^ (1- DBL_MANT_DIG) =
+          for IEEE:  = 2^-52 = DBL_EPSILON */
+            return DBL_EPSILON;
+
+        case 5: return M_LOG10_2;
+
+        default: return 0.0;
+    }
+}
+
+export function dF77_NAME(i: number): number {
+    return Rf_d1mach(i);
+}
+
+export function R_D_negInonint(x: number) {
+    return x < 0.0 || R_nonint(x);
+}
+
+export function R_nonint(x: number) {
+    return (fabs((x) - R_forceint(x)) > 1e-7 * fmax2(1., fabs(x)))
+}
+
+export function R_D_fexp(give_log: boolean, f: number, x: number): number {
+    return (give_log ? -0.5 * log(f) + (x) : exp(x) / sqrt(f));
+}
+
+
+/** bessel section */
+/** bessel section */
+/** bessel section */
+
+export const nsig_BESS = 16;
+export const ensig_BESS = 1e16;
+export const rtnsig_BESS = 1e-4;
+export const enmten_BESS = 8.9e-308;
+export const enten_BESS = 1e308;
+
+export const exparg_BESS = 709.;
+export const xlrg_BESS_IJ = 1e5;
+export const xlrg_BESS_Y = 1e8;
+export const thresh_BESS_Y = 16.;
+
+export const xmax_BESS_K = 705.342/* maximal x for UNscaled answer */
+
+
+/* sqrt(DBL_MIN) =	1.491668e-154 */
+export const sqxmin_BESS_K = 1.49e-154;
+
+/* x < eps_sinc	 <==>  sin(x)/x == 1 (particularly "==>");
+  Linux (around 2001-02) gives 2.14946906753213e-08
+  Solaris 2.5.1		 gives 2.14911933289084e-08
+*/
+export const M_eps_sinc = 2.149e-8;
+
+
+export function R_pow_di(x: number, n: number) {
+    let pow: number = 1.0;
+
+    if (ISNAN(x)) return x;
+    if (n != 0) {
+        if (!R_FINITE(x)) return R_pow(x, n);
+        if (n < 0) { n = -n; x = 1 / x; }
+        for (; ;) {
+            if (n & 1) pow *= x;
+            if (n >>= 1) x *= x; else break;
+        }
+    }
+    return pow;
+}
+
+export function R_pow(x: number, y: number): number { /* = x ^ y */
+
+    /* squaring is the most common of the specially handled cases so
+       check for it first. */
+    if (y == 2.0)
+        return x * x;
+    if (x == 1. || y == 0.)
+        return (1.);
+    if (x == 0.) {
+        if (y > 0.) return (0.);
+        else if (y < 0) return (ML_POSINF);
+        else return (y); /* NA or NaN, we assert */
+    }
+    if (R_FINITE(x) && R_FINITE(y)) {
+        /* There was a special case for y == 0.5 here, but
+           gcc 4.3.0 -g -O2 mis-compiled it.  Showed up with
+           100^0.5 as 3.162278, example(pbirthday) failed. */
+        return pow(x, y);
+    }
+    if (ISNAN(x) || ISNAN(y))
+        return (x + y);
+    if (!R_FINITE(x)) {
+        if (x > 0)               /* Inf ^ y */
+            return (y < 0.) ? 0. : ML_POSINF;
+        else {                  /* (-Inf) ^ y */
+            if (R_FINITE(y) && y == floor(y)) /* (-Inf) ^ n */
+                return (y < 0.) ? 0. : (myfmod(y, 2.) ? x : -x);
+        }
+    }
+    if (!R_FINITE(y)) {
+        if (x >= 0) {
+            if (y > 0)           /* y == +Inf */
+                return (x >= 1) ? R_PosInf : 0.;
+            else                /* y == -Inf */
+                return (x < 1) ? R_PosInf : 0.;
+        }
+    }
+    return NaN; // all other cases: (-Inf)^{+-Inf, non-int}; (neg)^{+-Inf}
+}
+
+
+export const R_finite = (x: number) => !Number.isFinite(x);
+
+/* C++ math header undefines any isnan macro. This file
+   doesn't get C++ headers and so is safe. */
+export const R_isnancpp = (x: number) => ISNAN(x);
+
+export function myfmod(x1: number, x2: number) {
+
+    let q = x1 / x2;
+    return x1 - floor(q) * x2;
+}
+
+
+export function R_powV(x: number, y: number): number /* = x ^ y */ {
+    if (x == 1. || y == 0.)
+        return (1.);
+    if (x == 0.) {
+        if (y > 0.) return (0.);
+    /* y < 0 */return (ML_POSINF);
+    }
+    if (R_FINITE(x) && R_FINITE(y))
+        return (pow(x, y));
+    if (ISNAN(x) || ISNAN(y)) {
+        return (x + y);
+    }
+    if (!R_FINITE(x)) {
+        if (x > 0)		/* Inf ^ y */
+            return ((y < 0.) ? 0. : ML_POSINF);
+        else {			/* (-Inf) ^ y */
+            if (R_FINITE(y) && y == floor(y)) /* (-Inf) ^ n */
+                return ((y < 0.) ? 0. : (myfmod(y, 2.) ? x : -x));
+        }
+    }
+    if (!R_FINITE(y)) {
+        if (x >= 0) {
+            if (y > 0)		/* y == +Inf */
+                return ((x >= 1) ? ML_POSINF : 0.);
+            else		/* y == -Inf */
+                return ((x < 1) ? ML_POSINF : 0.);
+        }
+    }
+    return (ML_NAN);		/* all other cases: (-Inf)^{+-Inf,
+                   non-int}; (neg)^{+-Inf} */
+}
+
+
+export const NA_REAL = ML_NAN;
+export const R_PosInf = ML_POSINF;
+export const R_NegInf = ML_NEGINF;
+
+export function REprintf(fmt: string, ...args: any[]) {
+    let args2 = Array.from(args);//.slice(1);
+    console.error.call(console.error, fmt, args2);
+}
+
+
+//  return x * Math.pow(2,y)
+export function ldexp(x: number, y: number): number {
+
+
+    if (ISNAN(x) || ISNAN(y)) {
+        return (x + y);
+    }
+    if (!R_FINITE(x) || !R_FINITE(y)) {
+        return ML_POSINF;
+    }
+    return x * Math.pow(2, y);
+
+}
+
+export const FLT_RADIX = 2;
+export const CHAR_BIT = 8;
+export const DBL_MAX_EXP = Math.log2(Number.MAX_VALUE);
+export const DBL_MIN_EXP = Math.log2(Number.MIN_VALUE);
+export const FLT_MAX_EXP = DBL_MAX_EXP;
+export const FLT_MIN_EXP = DBL_MIN_EXP;
+export const sizeofInt = 4 * Math.ceil(Math.log(Number.MAX_SAFE_INTEGER) / Math.log(2) / 4 / CHAR_BIT);
+
+export function Rf_i1mach(i: number): number {
+
+    switch (i) {
+        case 1: return 5;
+        case 2: return 6;
+        case 3: return 0;
+        case 4: return 0;
+
+        case 5: return CHAR_BIT * sizeofInt;
+        case 6: return sizeofInt;
+
+        case 7: return 2;
+        case 8: return CHAR_BIT * sizeofInt - 1;
+        case 9: return INT_MAX;
+
+        case 10: return FLT_RADIX;
+
+        case 11: return FLT_MANT_DIG;
+        case 12: return FLT_MIN_EXP;
+        case 13: return FLT_MAX_EXP;
+
+        case 14: return DBL_MANT_DIG;
+        case 15: return DBL_MIN_EXP;
+        case 16: return DBL_MAX_EXP;
+
+        default: return 0;
+    }
+}
+
+export function iF77_NAME(i: number) {
+    return Rf_i1mach(i);
+}
+

lib/_unif_random.doc.txt

@@ -0,0 +0,0 @@ // email from George Marsaglia

lib/_unif_random.ts

@@ -0,0 +0,0 @@ //park node crypto in diff namespace

lib/bd0.ts

@@ -0,0 +0,0 @@ /*

lib/bessel_j.ts

@@ -76,5 +76,2 @@ /*
 
-
-
-
 // unused now from R
@@ -81,0 +78,0 @@ function bessel_j(x: number, alpha: number): number {

lib/bessel_k.ts

@@ -0,0 +0,0 @@ /*

lib/bessel_y.ts

@@ -0,0 +0,0 @@ /*

lib/beta.ts

@@ -47,13 +47,21 @@ /*
 
-import {ISNAN, R_FINITE, ML_POSINF,ML_ERR_return_NAN, ML_ERROR, ME} from "./_general"
-import {gammafn} from "./gamma"
-import { lbeta } from "./lbeta"
+import {
+    ISNAN,
+    R_FINITE,
+    ML_POSINF,
+    ML_ERR_return_NAN,
+    ML_ERROR,
+    ME
+} from './_general';
 
+import { gammafn } from './gamma_fn';
+import { lbeta } from './lbeta';
+
 //const xmin =  - 170.5674972726612;
-const xmax =   171.61447887182298;
+const xmax = 171.61447887182298;
 const lnsml = - 708.39641853226412;
-   
 
-export function beta(a:number, b:number):number {
 
+export function beta(a: number, b: number): number {
+
     /*#ifdef NOMORE_FOR_THREADS
@@ -74,3 +82,3 @@ static double xmin, xmax = 0;//-> typically = 171.61447887 for IEEE
     if (ISNAN(a) || ISNAN(b)) return a + b;
-   
+
     if (a < 0 || b < 0)
@@ -92,3 +100,3 @@ return ML_ERR_return_NAN()
     } else {
-        let val:number = lbeta(a, b);
+        let val: number = lbeta(a, b);
         // underflow to 0 is not harmful per se;  exp(-999) also gives no warning
@@ -163,2 +171,2 @@ //#ifndef IEEE_754
 }
-*/
+*/

lib/chebyshev.ts

@@ -52,4 +52,6 @@ /*
 
-import { fabs, NaN } from "./_general"
 
+
+import { NaN, fabs } from './_general';
+
 export function chebyshev_init(dos: number[], nos: number, eta: number): number {
@@ -79,3 +81,6 @@ let i: number;
 
-    let b0: number, b1: number, b2: number, twox: number;
+    let b0: number;
+    let  b1: number;
+    let  b2: number;
+    let  twox: number;
     let i: number;
@@ -82,0 +87,0 @@

lib/cospi.ts

@@ -0,0 +0,0 @@ /*

lib/dunif.ts

@@ -0,0 +0,0 @@ /*

lib/gamma_cody.ts

@@ -0,0 +0,0 @@ /*

lib/lbeta.ts

 /*
+ *  AUTHOR
+ *  Jacob Bogers, [e-mail]
+ *  March 2, 2017
+ * 
+ *  ORIGINAL C-CODE AUTHOR (R Project)
  *  Mathlib : A C Library of Special Functions
  *  Copyright (C) 1998 Ross Ihaka
- *  Copyright (C) 2000-12 The R Core Team
- *  Copyright (C) 2003 The R Foundation
+ *  Copyright (C) 2000-2013 The R Core Team
+ *  Copyright (C) 2002-2004 The R Foundation
  *
@@ -36,18 +41,28 @@ *  This program is free software; you can redistribute it and/or modify
 
-import { ISNAN, R_FINITE, ML_POSINF, ML_ERR_return_NAN, ML_NEGINF, M_LN_SQRT_2PI } from './_general';
+import { 
+
+    ISNAN, 
+    R_FINITE, 
+    ML_POSINF, 
+    ML_ERR_return_NAN, 
+    ML_NEGINF, 
+    M_LN_SQRT_2PI 
+
+} from './_general';
+
 import { lgammacor } from './lgammacor';
-import { lgammafn } from './lgamma';
-import { gammafn } from './gamma';
+import { lgammafn } from './lgamma_fn';
+import { gammafn } from './gamma_fn';
 
 
 export function lbeta(a: number, b: number): number {
-    let corr: number, p: number, q: number;
+    let corr: number;
+    let  p: number;
+    let  q: number;
 
-    //#ifdef IEEE_754
     if (ISNAN(a) || ISNAN(b))
         return a + b;
-    //#endif
     p = q = a;
-    if (b < p) p = b;// := min(a,b) 
-    if (b > q) q = b;// := max(a,b) 
+    if (b < p) p = b; // := min(a,b) 
+    if (b > q) q = b; // := max(a,b) 
 
@@ -57,3 +72,3 @@ // both arguments must be >= 0
         return ML_ERR_return_NAN();
-    else if (p == 0) {
+    else if (p === 0) {
         return ML_POSINF;
@@ -134,2 +149,2 @@ }
 }
-*/
+*/

lib/lgammacor.ts

@@ -52,3 +52,3 @@ /*
 
-import { ME, ML_ERROR, ML_ERR_return_NAN } from './_general'
+import { ME, ML_ERROR, ML_ERR_return_NAN } from './_general';
 import { chebyshev_eval } from './chebyshev';
@@ -74,5 +74,5 @@
 
-const nalgm = 5
-const xbig = 94906265.62425156
-const xmax = 3.745194030963158e306
+const nalgm = 5;
+const xbig = 94906265.62425156;
+const xmax = 3.745194030963158e306;
 
@@ -88,3 +88,3 @@ export function lgammacor(x: number) {
     if (x < 10)
-        return ML_ERR_return_NAN()
+        return ML_ERR_return_NAN();
     else if (x >= xmax) {
@@ -145,2 +145,2 @@ ML_ERROR(ME.ME_UNDERFLOW, 'lgammacor');
 }
-*/
+*/

lib/runif.ts

@@ -0,0 +0,0 @@ /*

lib/sexp.ts

@@ -0,0 +0,0 @@ /*  AUTHOR

lib/stirlerror.ts

@@ -43,3 +43,3 @@ /*
 import {M_LN_SQRT_2PI} from './_general';
-import {lgammafn} from './lgamma';
+import {lgammafn} from './lgamma_fn';
 
@@ -46,0 +46,0 @@ const sferr_halves: number[] = [

package.json

 {
   "name": "lib-r-math.js",
-  "version": "1.0.13",
+  "version": "1.0.14",
   "description": "Javascript Pure Implementation of Statistical R \"core\" numerical libRmath.so",
@@ -20,3 +20,6 @@ "main": "index.js",
     "distribution",
-    "statistic"
+    "statistic",
+    "special functions",
+    "bessel function",
+    "data science"
   ],
@@ -23,0 +26,0 @@ "author": "Jacob Bogers",

README.md

@@ -20,2 +20,32 @@ # libRmath.js
 |------------------|--------------------|-------------|--------------------|
+| Toms708.java | ./lib/Toms708.ts | 14 March 2017 | from Java Version  James Curran ([e-mail]) (Java version)  |
+| pbeta.c | ./lib/pbeta.ts | 14 March 2017 | beta distribution function  |
+| pnorm.c| ./lib/pnorm.ts | 9 March 2017 |  Normal distribution function |
+| gammalims.c | ./lib/gammalims.ts | 5 march 2017 | calculates legal bounds of gamme_fn|
+| fround.c | ./lib/fround.ts | 5 march 2017 | rounds off to a set number of digites |
+| fprec.c | ./lib/fprec.ts | 4 march 2017 |  Returns the value of x rounded to "digits" significant |
+| expm1.c | ./lib/expm1.ts | 4 march 2017  | Compute the Exponential minus 1 |
+| dweibull.c | ./lib/dweibull.ts | 4 march 2017  | The density function of the Weibull distribution.|
+| dt.c | ./lib/dt.ts| 4 March 2017 |  The t density |
+| dpois.c | ./lib/dpois.ts | 4 March 2017 |  dpois() computes the Poisson probability  lb^x exp(-lb) / x! |
+| dnchisq.c | ./lib/dnchisq.ts |  The density of the noncentral chi-squared distribution with "df" |
+| dnt.c | ./lib/dnt.ts| 4 March 2017 |  Computes the density of the noncentral beta distribution with |
+| dnorm.c | ./lib/dnorm.ts | 25 feb 2017 | Compute the density of the normal distribution. |
+| dnf.c | ./lib/dnt.ts | 25 feb 2017  | The density function of the non-central F distribution |
+| dnbinom.c | ./lib/dnbinom.ts | 25 feb 2017 | Computes the negative binomial distribution. |
+| dlogis.c | ./lib/dlogis.ts | 4 March 2017 | not sure what it does |
+| dlnorm.c | ./lib/dlnorm.ts |4 March 2017|The density of the lognormal distribution.|
+| dhyper.c | ./lib/dhyper.ts | 4 March 2017 |  The hypergeometric probability |
+| dgeom.c | ./lib/dgeom.ts | 4 March 2017 |   Computes the geometric probabilities, Pr(X=x) = p(1-p)^x. |
+| dnbeta.c | ./lib/dnbeta.ts | 4 March 2017 |  Computes the density of the noncentral beta distribution with |
+| pgamma.c | ./lib/pgamme.ts | 9 March 2017 | This function computes the distribution function for the gamma distribution |
+| dgamma.c | ./lib/dgamma.ts | 27 feb 2017 |  Computes the density of the gamma distribution |
+| lbeta.c | ./lib/lbeta.ts | March 2 2017 |  This function returns the value of the log beta function.|
+
+| C99 gamma function | ./lib/c99_gamma.ts | 25 feb 2017 | added C99 gamma and lgamma, |
+|dnbinom.c | ./lib/dnbinom.ts | 25 feb 2017 | negative binomial distribution.
+|dbeta.c           |  ./lib/dbeta.ts | 25 feb 2017  | R "dbeta" beta distribution function  |
+|dbinom.c           | ./lib/dbinom.ts  | 25 feb 2017 | probability mass function of binomial distribution |
+|log1p.c | ./lib/log1p.ts | 25 feb 2017| calculate log(1+x) for small value of x|
+|choose.c           | choose.ts | 21 feb 2017 | R "choose" function, C(n,k) binomial coefficients |
 |gamma_cody.c      | gamme_cody.ts| 19 feb 2017| GAMMA function using algo of  W. J. Cody, |
@@ -30,8 +60,8 @@ |bessel_i.c           | bessel_i.ts  | 19 feb 2017 | besseli |
 |runif.c           | ./runif.ts| 4-feb-2017 | implemented 3 RNG and native browser/node agnostic 64 RNG map to floating number |
-|bd0.c           | ./lib/bd0.ts |23-jan-2017 | hidden, used by modules dbinom.c ,dpois.c dt.c |  
+|bd0.c           | ./lib/bd0.ts |23-jan-2017 | hidden, used by modules dbinom.c ,dpois.c dt.c |
 |beta.c           |./lib/beta.ts  | 23-jan-2017 | [beta](https://en.wikipedia.org/wiki/Beta_function) |
 |chebyshev.c           | ./lib/chebyshev.ts | 23-jan-2017 | chebyshev\_init , chebyshev\_eval |
 |cospi.c           | ./lib/cospi.ts | 23-jan-2017 | cospi, sinpi, tanpi |
-|gamma.c           |./lib/gamma.ts | 23-jan-2017 | [gammafn] gamme function(https://en.wikipedia.org/wiki/Gamma_function) |
-|lgamma.c           | ./lib/lgamma.ts | 23-jan-2017 | logarithmic gamma [lgammafn](https://en.wikipedia.org/wiki/Gamma_function) |
+|gamma.c           |./lib/gamma_fn.ts | 23-jan-2017 | [gammafn] gamme function(https://en.wikipedia.org/wiki/Gamma_function) |
+|lgamma.c           | ./lib/lgamma_fn.ts | 23-jan-2017 | logarithmic gamma [lgammafn](https://en.wikipedia.org/wiki/Gamma_function) |
 |lgammacor.c           |./lib/lgammecor.ts  | 23-jan-2017 | lgammacor |
@@ -50,9 +80,9 @@ |stirlerr.c           | ./lib/stirlerr | 23-jan-2017 | Computes the log of the error term in Stirling's formula ( _stirlerr_ ) |
 bessel_y.c           | done | no | R "bessely" gives the Bessel function of the second kind . |
-beta.c           |done ./lib/beta.ts  | no | [beta](https://en.wikipedia.org/wiki/Beta_function) |
+beta.c           |done   | no | [beta](https://en.wikipedia.org/wiki/Beta_function) |
 chebyshev.c           | done ./lib/chebyshev.ts | no | chebyshev\_init , chebyshev\_eval |
-choose.c           |TODO | | |
+choose.c           |done  | no | R "choose" function, C(n,k) binomial coefficients |
 cospi.c           | done ./lib/cospi.ts | no| cospi, sinpi, tanpi |
-d1mach.c           |TODO | | |
-dbeta.c           |  TODO |  | |
-dbinom.c           | TODO| | |
+d1mach.c           |done | no | included in ./_general.ts |
+dbeta.c           |  done | no  | distribution function of beta |
+dbinom.c           | done  | no | probability mass function of binomial distribution |
 dcauchy.c           | TODO| | |
@@ -62,36 +92,36 @@ dchisq.c           | TODO| | |
 df.c           | TODO| | |
-dgamma.c           | TODO| | |
-dgeom.c           |TODO | | |
-dhyper.c           |TODO | | |
+dgamma.c           | done| no  |  Computes the density of the gamma distribution, |
+dgeom.c           |done |no  | Computes the geometric probabilities, Pr(X=x) = p(1-p)^x |
+dhyper.c           |done | no  |  The hypergeometric probability |
 dlnorm.c           |TODO | | |
 dlogis.c           | TODO| | |
-dnbeta.c           |TODO | | |
-dnbinom.c           |TODO | | |
+dnbeta.c           |done | no |  Computes the density of the noncentral beta distribution with |
+dnbinom.c           |done | no  | negative binomial probability prob mass function |
 dnchisq.c           |TODO | | |
-dnf.c           |TODO | | |
-dnorm.c           |TODO | | |
-dnt.c           |TODO | | |
-dpois.c           | TODO| | |
-dt.c           |TODO | | |
+dnf.c           |done | no | The density function of the non-central F distribution |
+dnorm.c           |done  | no  |  Compute the density of the normal distribution. |
+dnt.c           |done | no | the non-central t density |
+dpois.c           | done| no  |  dpois() computes the Poisson probability  lb^x exp(-lb) / x! |
+dt.c           |done | no |  The t density  |
 dunif.c           | done| no | R "dunif" function  |
-dweibull.c           | TODO| | |
-expm1.c           |TODO | | |
+dweibull.c           | done| no  |  The density function of the Weibull distribution. |
+expm1.c           |done | no  | Compute the Exponential minus 1 |
 fmax2.c           |TODO | | |
 fmin2.c           | TODO| | |
-fprec.c           |TODO | | |
-fround.c           |TODO | | |
+fprec.c           |done  | no |  Returns the value of x rounded to "digits" significant  |
+fround.c           |done | no | fround function |
 fsign.c           |TODO | | |
 ftrunc.c           | TODO| | |
-gamma.c           |done  ./lib/gamma.ts | no | [gammafn](https://en.wikipedia.org/wiki/Gamma_function) |
+gamma.c           |done  ./lib/gamma_fn.ts | no | [gammafn](https://en.wikipedia.org/wiki/Gamma_function) |
 gamma_cody.c           | done| no | GAMMA function using algo of  W. J. Cody, |
-gammalims.c           |TODO | | |
+gammalims.c           |done | no | calculates legal bounds of gamma_fn |
 i1mach.c           |TODO | | |
 imax2.c           |TODO | | |
 imin2.c           | TODO| | |
-lbeta.c           | TODO| | |
-lgamma.c           | done ./lib/lgamma.ts | no | logarithmic gamma [lgammafn](https://en.wikipedia.org/wiki/Gamma_function) |
+lbeta.c           | done| no  |  This function returns the value of the log beta function. |
+lgamma.c           | done ./lib/lgamma_fn.ts | no | logarithmic gamma [lgammafn](https://en.wikipedia.org/wiki/Gamma_function) |
 lgammacor.c           |done ./lib/lgammecor.ts  | no | lgammacor |
-log1p.c           |TODO | | |
+log1p.c           | done | no  | calculate log(1+x) with high accuracy for small x |
 mlutils.c           |TODO | | |
-pbeta.c           |TODO | | |
+pbeta.c           |done | no  | pBeta distribution function |
 pbinom.c           |TODO | | |
@@ -102,3 +132,3 @@ pcauchy.c           | TODO| | |
 pf.c           |TODO | | |
-pgamma.c           |TODO | | |
+pgamma.c           |done | no  | 	This function computes the distribution function for the	gamma distribution  |
 pgeom.c           | TODO| | |
@@ -112,3 +142,3 @@ phyper.c           |TODO | | |
 pnf.c           |TODO | | |
-pnorm.c           | TODO| | |
+pnorm.c           | done| no  |  normal distribution function |
 pnt.c           | TODO| | |
@@ -167,4 +197,4 @@ polygamma.c           | TODO| | |
 stirlerr.c           | done ./lib/stirlerr | no | Computes the log of the error term in Stirling's formula ( _stirlerr_ ) |
-toms708.c           |TODO | | |
+toms708.c           |NAP | no | ported instead Java Version  from James Curran ([e-mail]) (Java version) |
 wilcox.c           | TODO| | |
 

tsconfig.json

@@ -0,0 +0,0 @@ {

tslint.json

@@ -0,0 +0,0 @@ {

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