# Distributome Resource Database
#
# http://Distributome.org
# http://Distributome.org/jars/implementedDistributome.txt
# current Node format is "id; name; type,type; formula_id; url; keywords; references" 
# current Edge format is "label; name; type,type; formula_id; from_nodeId; to_nodeId; references" 
#
# Node (distribution) Types will be (full-name & abbreviation): 
# 0 No Type Given 
# 1 Convolution (Conv) 
# 2 Memoryless (Mless) 
# 3 Inverse (Inv) 
# 4 Linear Combination (LinComb) 
# 5 Minimum (min) 
# 6 Maximum (max) 
# 7 Product (Prod) 
# 8 Conditional Residual (CondRes) 
# 9 Scaling (Scale) 
# 10 Simulate (Sim) 
# 11 Variate Generation(VGen)
#
# Edge Types (directional distribution relations) will be: 
# 0 No Type Given 
# 1 Special Case (SC) 
# 2 Transform (T) 
# 3 Limiting (Lim) 
# 4 Bayesian (Bayes) 

#Version Info
[otherInfo]
version = 1.0

# Node syntax format is "id; name; type,type; formula_id; url; keywords; references" 
[nodes] 
url_prefix = http://socr.ucla.edu/htmls/dist/ 
Node = 1; Standard Normal; 0; 1; Normal_Distribution.html; continuous, symmetric, infinite, exponential; 1, 2, 3
Node = 2; General Normal; 1,4,9;2; Normal_Distribution.html; continuous, symmetric, infinite, exponential; 1, 2, 3, 4
Node = 3; Chi; 0; 3; Chi_Distribution.html; continuous, nonsymmetric, positive; 2, 3
Node = 4; Chi-Square; 1; 4; ChiSquare_Distribution.html; continuous, nonsymmetric, positive; 2, 3, 4
Node = 5; Gamma; 1,9;5; Gamma_Distribution.html; continuous, nonsymmetric, positive, exponential; 2, 3, 6
Node = 6; Beta; 0;6; Beta_Distribution.html; continuous, nonsymmetric, finite; 2, 3, 5, 6
Node = 7; Student's T; 0; 7; StudentT_Distribution.html; continuous, symmetric, infinite; 2, 3
Node = 8; Poisson; 1; 8 ; Poisson_Distribution.html; discrete, nonsymmetric, positive; 2, 3
Node = 9; General Cauchy; 1,3,9,10; 9; GeneralCauchy_Distribution.html; continuous, symmetric, infinite; 2, 3
Node = 10; Cauchy; 3,9,10; 10; Cauchy_Distribution.html; continuous, symmetric, infinite; 2, 3
Node = 11; Exponential; 2,5,8,9,10; 11; Exponential_Distribution.html; continuous, nonsymmetric, positive, exponential; 2, 3
Node = 12; Fisher's F; 3; 12 ; Fisher_Distribution.html; continuous, nonsymmetric, infinite ; 2, 3, 5
Node = 13; Bernoulli; 5,6,7; 13; Bernoulli_Distribution.html; discrete, nonsymmetric, positive; 2, 3
Node = 14; Binomial; 1; 14; Binomial_Distribution.html; discrete, nonsymmetric, positive; 2, 3
Node = 15; Negative Binomial; 1; 15 ; NegativeBinomial_Distribution.html; discrete, nonsymmetric, positive; 2, 3
Node = 16; Geometric; 2,5,11; 16 ; Geometric_Distribution.html; discrete, nonsymmetric, positive; 2, 3
Node = 17; Erlang; 9; 17 ; Erlang_Distribution.html; continous, positive, nonsymmetric, exponential; 2, 3
Node = 18; Laplace; 11; 18; Laplace_Distribution.html; continuous, symmetric, infinite, exponential; 2, 3
Node = 19; Continuous Uniform; 8,11;19; ContinuousUniform_Distribution.html; continuous, symmetric, positive, finite; 2, 3
Node = 20; Discrete Uniform; 8,11;20; DiscreteUniform_Distribution.html; discrete, symmetric, positive, finite; 2, 3
Node = 21; Logarithmic-Series; 0;21; LogarithmicSeries_Distribution.html; discrete, nonsymmetric, infinite; 2, 7
Node = 22; Logistic; 9, 11;22; Logistic_Distribution.html; continuous, symmetric, infinite; 2, 3
Node = 23; Logistic-Exponential; 9;23; LogisticExponential_Distribution.html; continuous, infinite; 2, 8
Node = 24; Power-Function; 6,9;24; PowerFunction_Distribution.html; continuous, nonsymmetric, finite; 2, 12
Node = 25; Benford's Law; 0;25; Benford_Distribution.html; continuous, nonsymmetrical, infinite; 2, 10
Node = 26; Pareto; 5; 26;Pareto_Distribution.html; continuous, nonsymmetric, finite; 2, 3
Node = 27; Student's T Non-Central; 0; 27;StudentT_Distribution.html; continuous, symmetric, infinite; 2
Node = 28; ArcSine; 0; 28;ArcSine_Distribution.html; continuous, symmetric, finite; 2,3
Node = 29; Half Circle; 0; 29;Circle_Distribution.html; continuous, symmetric, finite; 0
Node = 30; U-Quadratic; 0; 30;UQuadratic_Distribution.html; continuous, symmetric, finite; 0
Node = 31; Standard Uniform; 0; 31; ContinuousUniform_Distribution.html; continuous, symmetric, finite; 2, 3
Node = 32; Zipf; 0; 32; ZipfMandelbrot_Distribution.html; continuous, nonsymmetric, finite; 3
Node = 33; Inverted Gamma; 0; 33; InverseGamma_Distribution.html; continuous, nonsymmetric, finite, positive; 2
Node = 34; Fisher-Tippett; 0; 34; FisherTippett_Distribution.html; continuous, nonsymmetric, finite, positive; 0
Node = 35; Gumbel; 0; 35; Gumbel_Distribution.html; continuous, nonsymmetric, finite, positive; 0
Node = 36; Hypergeometric; 0; 36; HyperGeometric_Distribution.html; discrete, nonsymmetric, finite, positive; 2,3
Node = 37; Log-Normal; 7; 37; LogNormal_Distribution.html; continuous, nonsymmetric, infinite, positive; 2, 3
Node = 38; Gibrat's; 0; 38; Gilbrats_Distribution.html; continuous, nonsymmetric, finite, positive; 0
Node = 39; Hyperbolic Secant; 10; 39; HyperbolicSecant_Distribution.html; continuous, symmetric, infinite, positive; 2 
Node = 40; Gompertz; 0; 40; Gompertz_Distribution.html; continuous, nonsymmetric, finite, positive; 0
Node = 41; Standard Cauchy; 3,9,10; 41; Cauchy_Distribution.html; continuous; symmetric, finite; 2, 3


# Edge syntax format is "label; name; type,type; formula_id; from_nodeId; to_nodeId; references" 
[edges] 
Edge = 1; Standard Normal to General Normal Transformation; 1,2; 1001; 1; 2; 1, 2, 3
Edge = 2; General Normal to Standard Normal Transformation; 2; 1002; 2; 1; 1, 2, 3
Edge = 3; Standard Normal to Chi Transformation; 2; 1003; 1; 3; 2, 3
Edge = 4; Standard Normal to Chi-Square Transformation; 2; 1004; 1; 4; 2, 3, 4
Edge = 5; Gamma to Normal Transformation; 3; 1005; 5; 2; 2, 3
Edge = 6; Gamma to Exponential Transformation; 1; 1006; 5; 11; 2, 3
Edge = 7; Gamma to Beta Transformation; 2; 1007; 5; 6; 2, 3, 6
Edge = 8; Student's T to Standard Normal Transformation; 3; 1008; 7; 1; 2, 3
Edge = 9; Student's T to Cauchy Transformation; 1; 1009; 7; 10; 2, 3
Edge = 10; Cauchy to General Cauchy Transformation; 1,2; 1010; 10; 9; 2, 3
Edge = 11; General Cauchy to Cauchy Transformation; 2; 1011; 9; 10; 2, 3
Edge = 12; Fisher's F to Student's T Transformation; 2; 1012; 12; 7; 2, 3
Edge = 13; Student's T to Fisher's F Transformation; 2; 1013; 7; 12; 2, 3
Edge = 14; Bernoulli to Binomial Transformation; 1,2; 1014; 13; 14; 2, 3
Edge = 15; Binomial to Bernoulli Transformation; 1,2; 1015; 14; 13; 2, 3
Edge = 16; Binomial to General Normal Transformation; 3; 1016; 14; 2; 2, 3
Edge = 17; Binomial to Poisson Transformation; 3; 1017; 14; 2; 2, 3
Edge = 18; Negative Binomial to Geometric Transformation; 1; 1018; 15; 16; 2, 3
Edge = 19; Erlang to Exponential Transformation; 1; 1019; 17; 11; 2, 3
Edge = 20; Erlang to Chi-Squared Transformation; 1; 1020; 17; 4; 2 ,3
Edge = 21; Laplace to Exponential Transformation; 1, 2; 1021; 18; 11; 2, 3
Edge = 22; Exponential to Laplace Transformation; 1; 1022; 11; 18; 2, 3
Edge = 23; Beta to Arcsine Transformation; 0; 1023; 6; 28; 2, 3
Edge = 24; Noncentral Student's T to Normal; 3; 1024; 27; 2; 2,3
Edge = 25; Noncentral Student's T to Student's T; 1; 1025; 27; 7; 2,3
Edge = 26; Pareto to Exponential; 2; 1026; 26; 11; 2,3
Edge = 27; Logistic Exponential to Exponential; 1; 1027; 23; 11; 2, 8
Edge = 28; Standard Uniform to Pareto; 2; 1028; 31; 26; 2
Edge = 29; Standard Uniform to Benford; 2; 1029; 31; 25; 2
Edge = 30; Standard Uniform to Exponential; 2,3; 1030; 31; 11; 2, 3
Edge = 31; Standard Uniform to Logistic Exponential; 2; 1031; 31; 23; 2
Edge = 32; Standard Uniform to Beta; 1; 1032; 31; 6; 2, 3
Edge = 33; Continuous Uniform to Standard Uniform; 1; 1033; 19; 31; 2, 3
Edge = 34; Zipf to Discrete Uniform; 1; 1034; 32; 20; 2
Edge = 35; Poisson to Normal; 3; 1035; 8; 1; 2, 3
Edge = 36; Binomial to Poisson; 3; 1036; 14; 8; 2, 3
Edge = 37; Gamma to Inverted Gamma; 2; 1037; 5; 33; 2
Edge = 38; Fisher-Tippett to Gumbel; 1; 1038; 34; 35; 0
Edge = 39; Hypergeometric to Binomial; 3; 1039; 36; 14; 2,3
Edge = 40; Log-Normal to Normal; 2; 1040; 37; 2; 2,3
Edge = 41; Normal to Log-Normal; 2; 1041; 2; 37; 2,3
Edge = 42; Log-Normal to Gibrat's; 1; 1042; 37; 38; 0
Edge = 43; Cauchy to Standard Cauchy; 1; 1043; 10; 41; 2,3
Edge = 44; Standard Cauchy to Cauchy; 2; 1044; 41; 10; 2,3
Edge = 45; Standard Cauchy to Hyperbolic Secant; 2; 1045; 41; 39; 2


# Formula syntax format is "id; density; formula;"
[formulas]
density_prefix = http://wiki.stat.ucla.edu/socr/uploads/math/ 
Formula = 1; 0/c/a/0cab65bf1790276ad1d97ab46a40567f.png; f(x)= {e^{-x^2} \over \sqrt{2 \pi}}
Formula = 2; 9/8/7/987fd149835d1de389765cdf2d03e247.png; f(x)= {e^{{-(x-\mu)^2} \over 2\sigma^2} \over \sqrt{2 \pi\sigma^2}}
Formula = 3; d/7/1/d71a0585ec10d96b0398de15a17647d9.png; \frac{2^{1-k/2}x^{k-1}e^{-x^2/2}}{\Gamma(k/2)}
Formula = 4; b/e/f/bef279b2cb4f25a855b38092b3dc671b.png; \frac{(1/2)^{k/2}}{\Gamma(k/2)} x^{k/2 - 1} e^{-x/2}\,
Formula = 5; 2/b/1/2b123f5be4f5c152db65389455d3e2de.png; x^{k-1} \frac{\exp{\left(-x/\theta\right)}}{\Gamma(k)\,\theta^k}\,\!
Formula = 6; 5/8/b/58b0965234c4a32bf55111fe2ad12535.png; \frac{\Gamma(\alpha+\beta)}{\Gamma(\alpha)\Gamma(\beta)}\, x^{\alpha-1}(1-x)^{\beta-1}\!
Formula = 7; f/6/d/f6dbd1429a3d5f065980c11ed57254b1.png; \frac{\Gamma(\frac{\nu+1}{2})} {\sqrt{\nu\pi}\,\Gamma(\frac{\nu}{2})} \left(1+\frac{x^2}{\nu} \right)^{-(\frac{\nu+1}{2})}\!
Formula = 8; 9/9/2/9928c50bbeac8192fa2414d10faf1377.png; \frac{e^{-\lambda} \lambda^k}{k!}\!
Formula = 9; a/9/2/a9260c6814d86ac3231f3934db752577.png; \frac{1}{\pi\gamma \left[1 + \left(\frac{x-x_0}{\gamma}\right)^2\right]}
Formula = 10; a/9/2/a9260c6814d86ac3231f3934db752577.png; \frac{1}{\pi\gamma \left[1 + \left(\frac{x-x_0}{\gamma}\right)^2\right]}
Formula = 11; 1/7/6/1764a5aca4ec3b78d60d46a724dcd5ec.png; \lambda e^{-\lambda x},\; x \ge 0
Formula = 12; b/b/b/bbb4079319994e3d46d43ae12510e74b.png; \frac {(\frac {d_1 x}{d_1 x + d_2})^{ d_1/2} ( 1 - \frac {d_1 x} {d_1 x + d2}) ^ {d_2/2}} { xB(d_1/2 , d_2/2) }
Formula = 13; 8/6/7/867103cbcf2d8f2a84e015ae4297df74.png; f(k;p) \begin{cases} \mbox{p if k = 1,} \mbox{1 - p if k = 0,} \mbox{0 otherwise} \end{cases} 
Formula = 14; 4/6/f/46faf4c680409bf76d69404e34a678d0.png; \begin{pmatrix} n  \\ k \end{pmatrix} p^k (1-p)^{n-k}
Formula = 15; 8/1/f/81f96673ef90b51ab48d3ca77f310ac8.png; \begin{pmatrix} k + r - 1 \\ k \end{pmatrix} p^r(1-p)^k
Formula = 16; a/4/a/a4a4a23832ba0edbdaf9e226c2ac02c1.png;\begin{pmatrix} 1-p \end{pmatrix} ^{k-1}p
Formula = 17; a/0/2/a0244739ba01e615049257a28de4fdd5.png; \frac {\lambda x^{k-1}e^{-\lambda x}} {(k-1)!}
Formula = 18; a/d/3/ad36da6a4fcc7c6f4acd08062ca9fdab.png; \frac {1}{2b} \exp (- \frac{|x-\mu|}{b}) 
Formula = 19; 8/6/6/8669d896dcbf0134e37cff56ff424f61.png; f(x) = \begin{cases} \frac{1}{b-a} \mbox{ for } a \le x \le b \\ 0 \mbox{ for } x < a \mbox{ or } x > b \end{cases}
Formula = 20; 2/5/7/2579584dc45cf3f73dea42ba8265062e.png; f(x) = \begin{cases} 1/n \mbox{ for } a \le x \le b, \\  0 \mbox{ otherwise} \end{cases} 
Formula = 21; f/2/0/f2061904fabaa091a2a6de94d67ad00d.png; f(k) = \frac{-1}{ln(1-p)} \frac{p^k}{k} 
Formula = 22; 5/3/a/53ad61d172e22491bbd974961830ed60.png; f(x;u,s) = \frac{e^{-(x-\mu)/s}} {s(1+e^{-(x-\mu)/s})^2}
Formula = 23; c/0/b/c0bbb7c859640450d9e0f2598a4565c9.png; f(x;\beta) = \frac { \beta e^x(e^x - 1)^{\beta-1}} {(1+(e^x-1)^\beta))^2} \mbox{   }\mbox{   }x, \beta > 0 
Formula = 24; c/8/3/c83d7f43422655121c3a3a5c2adb4037.png; f(x) = \frac {\alpha(x-a)^{\alpha-1}} {(b-a)^\alpha}
Formula = 25; e/2/e/e2e118712196bf2670a51e0e59655f6f.png; P(d) = \log_b(d + 1)- \log_b(d) = \log_b(\frac{d + 1}{d})
Formula = 26; 5/d/2/5d2eb18ae43752138f3189ca9f7e7f8e.png; \frac {kx^k_m} {x^{k+1}}
Formula = 27; e/3/7/e37a9ea8dea4ca3d0d7d55f76aaa430b.png; f(t)=\frac{\nu^{\nu/2}e^{-\nu\mu^2/2(t^2+\nu)}} {\sqrt{\pi}\Gamma(\nu/2)2^{(\nu-1)/2}(t^2+\nu)^{(\nu+1)/2}} \times\int\limits_0^\infty x^\nu\exp\left[-\frac{1}{2}\left(x-\frac{\mu t}{\sqrt{t^2+\nu}}\right)^2\right]dx
Formula = 28; 1/4/7/147aa81e110d81ed11d1f3d51169bc78.png; f(x) = \frac{1}{\pi \sqrt{x(1-x)}}
Formula = 29; 4/5/a/45a7876ef35972bf28385be926c52b62.png; f(x)={2\sqrt{r^2 - x^2}\over \pi r^2 }, \forall x \in [-r , r]
Formula = 30; f/f/7/ff76cc91a9caab7bead2efe8e5d9402f.png; \alpha \left ( x - \beta \right )^2 
Formula = 31; 8/d/e/8dea828028c02208956348d4f00bb3e3.png; U(0,1) = f(x) = \begin{cases} {1} \mbox{ for } 0 \le x \le 1 \\ 0 \mbox{ for } x < 0 \mbox{ or } x > 1 \end{cases}
Formula = 32; d/9/7/d97d3fd7535620600d05c161b9864817.png; \frac{1/k^s}{H_{N,s}}
Formula = 33; 6/c/1/6c1d1b87912709db4a5adb09e5ed05bb.png; \frac{\beta^\alpha}{\Gamma(\alpha)} x^{-\alpha - 1} \exp \left(\frac{-\beta}{x}\right)
Formula = 34; 5/3/d/53dee9edf9ef4de0fe9f8b9db33c0518.png; \frac{z\,e^{-z}}{\beta}\!</math><br /> where <math>z = e^{-\frac{x-\mu}{\beta}}\!
Formula = 35; 8/9/1/891506209f21b971fa769f3dcffcb344.png; f(x) = e^{-x} e^{-e^{-x}}.
Formula = 36; d/5/0/d50065813c1ddcec7fada21d7da3e8b2.png; {{{m \choose k} {{N-m} \choose {n-k}}}\over {N \choose n}}
Formula = 37; b/3/f/b3f2a95779f28c24a5a265ba6498ceec.png; \frac{1}{x\sigma\sqrt{2\pi}}\exp\left[-\frac{\left(\ln(x)-\mu\right)^2}{2\sigma^2}\right]
Formula = 38; d/0/3/d03d955b51d917ba307deef3c7e277a0.png; \frac{1}{\sigma\sqrt{2\pi}}\exp\left[-\frac{\left(\ln(x)\right)^2}{2\sigma^2}\right]
Formula = 39; f/d/7/fd732311789b812437374f24b9a435f1.png; \frac12 \; \operatorname{sech}\!\left(\frac{\pi}{2}\,x\right)\!
Formula = 40; 4/e/f/4efe11d1016f67a67761bf1697fb5a9b.png; b e^{-bx} e^{-\eta e^{-bx}}\left[1 + \eta\left(1 - e^{-bx}\right)\right]
Formula = 41; 3/f/6/3f633b544c30394c3315b0bcc8952a7c.png; f(x; 0,1) = \frac{1}{\pi (1 + x^2)}. \!

Formula = 1001; 8/0/d/80dced834e1436711a7c36c750f3f735.png; \mu+\sigma\times X
Formula = 1002; 8/3/5/83553ea7c89c2fb1bc767b20b6621bc8.png; X-\mu \over \sigma
Formula = 1003; 0/e/8/0e82d932802db75c69457c1f70121647.png; |\ X |
Formula = 1004; 7/7/d/77ddc26ca6d31693cf7a799fd68bcd71.png; \sum_{k=1}^{\nu} X_k^2
Formula = 1005; a/6/8/a688ec35461cfae90a022ca0def20859.png; \mu=\alpha\times\beta;\sigma^2=\alpha^2\times\beta;\beta\longrightarrow\infty
Formula = 1006; 8/a/b/8ab1451dcf17a3ba153506f89132f7fe.png; {\Gamma}(k=1, \theta=1/\lambda)\, is equivalent to exponential Exp(\lambda)
Formula = 1007; f/8/e/f8ed04a68db9bbcc413df33606112a0f.png; X_1 \over X_1 + X_2
Formula = 1008; b/0/d/b0dfc554d084bc343bf4263ca603c03e.png; n\longrightarrow\infty
Formula = 1009; 0/6/5/0657cf55d0b10d52b3e187d641de6abe.png; n=1 \ 
Formula = 1010; e/c/a/ecacf76de371e76659d34ad635216b91.png; a + \alpha\times X
Formula = 1011; 1/a/f/1af78bbc514c0c56cad9728118652f1c.png; a=0; \alpha=1 \ 
Formula = 1012; 9/c/7/9c7309b01498ce159946ef1b1d0b8b34.png; \sqrt X
Formula = 1013; 9/c/7/9c7309b01498ce159946ef1b1d0b8b34.png; X^2 
Formula = 1014; 5/2/3/52375f2d577439414ce23e89c0e90245.png; \sum X_i 
Formula = 1015; 3/0/9/309b6cc83615c322d03dd3a81146ccf7.png; \begin{pmatrix} n = 1 \end{pmatrix}
Formula = 1016; e/3/e/e3ee1b225f54d61cae44f421a343d150.png; \begin{vmatrix} \mu = np \\ \sigma^2 = np(1-p) \\n \rightarrow \infty \end{vmatrix}
Formula = 1017; a/c/b/acbb91e21faa9372b5e4c84b67e88563.png; \begin{vmatrix}\mu = np \\ n \rightarrow \infty \end{vmatrix}
Formula = 1018; 8/2/8/828d7447db469527f59027af2f0436fe.png; \begin{pmatrix} r = 1 \end{pmatrix} 
Formula = 1019; 1/d/9/1d97b0f3e191093d465db35e15ee3f5f.png; \begin{pmatrix} k = 1 \end{pmatrix}
Formula = 1020; f/4/c/f4c904dda6bf90e107ce01600450ff32.png; \begin{pmatrix} \alpha = 2 \end{pmatrix}
Formula = 1021; e/e/4/ee4c20b42a0a181b39363183c4a8cee9.png; \begin{pmatrix} \begin{vmatrix} X \end{vmatrix} \\ \alpha_1 = \alpha_2 \end{pmatrix}
Formula = 1022; b/2/a/b2a02a4fe050cf31125044e15375af66.png; x_1 - x_2 \ 
Formula = 1023; a/7/f/a7fbf470b9c6ca3cd95013edac0a0ec7.png; \alpha = \beta = \frac{1}{2}
Formula = 1024; c/5/9/c597e03be18f6338e0e9569b2421d1b5.png; Z=\lim_{\nu\to\infty}T
Formula = 1025; 4/5/5/45514bf83c017240216ab94cd4f9858a.png; \mu = 0 \
Formula = 1026; 5/2/4/524374e103e44732a253e8768e5215e6.png; log(X/\lambda) \
Formula = 1027; 4/7/8/4787ad09fc48180d72782c7a077a25c3.png; \beta = 1 
Formula = 1028; b/a/d/bad4767e39b51fd92b1da59cb7383e25.png; \lambda X ^{-1/K} \
Formula = 1029; 0/9/1/091ed70e275fbcc3297246784860f1de.png; 10^X \ 
Formula = 1030; e/c/f/ecf7482949cf856fecdcde907ceb2b87.png; n(1-X_{(n)}), n -> \infty 
Formula = 1031; b/b/1/bb14e96da3be11b8bee63fcfbb54fefa.png; \frac{log[1+(\frac{X}{1-X})^{1/K}]}{\lambda} 
Formula = 1032; f/1/2/f123f58ac6492e4f86b14d0cc3707716.png; Y = 1 - X^{1/n} \
Formula = 1033; e/d/d/edd898dff31897ca649d0b4590d84043.png; a = 0, b = 1 \
Formula = 1034; 5/e/6/5e67a79804119a79ed78668db6b4b9a6.png; a = 0, a = 1, b = n \
Formula = 1035; f/b/b/fbba1fb57c6fbbf25e2ed13f23e8d87d.png; \sigma ^2 = \mu , \mu \to \infty
Formula = 1036; a/a/3/aa38f2dab9b50225c09796bdcd578203.png; \mu = np, \mu \to \infty
Formula = 1037; a/8/8/a88fc269c828b5b436c0ef1022203c8a.png; \frac{1}{X}
Formula = 1038; f/a/6/fa67fd23924241eef6f37bc79d8cfbac.png; \mu = 0, \beta = 1 \ 
Formula = 1039; e/5/7/e5727837d8333f3201799fc4bee09c7d.png; p = \frac{n_1}{n_3}, n = n_2, n_3, n \to \infty \ 
Formula = 1040; 8/3/e/83e0d6816bafc1712cd7d548f9ded3dd.png; log(X) \ 
Formula = 1041; 6/5/9/659484f2421a5ee6582f5178672ee773.png; e^X \ 
Formula = 1042; 9/e/f/9efceaf8845cb579afa3453960f66389.png; \mu = 0, x = 1 \
Formula = 1043; d/b/3/db380d1c063dc3bd351557edfa81541c.png; \gamma = 1, x_0 = 0 \
Formula = 1044; 7/5/a/75a3819467ee5722defef46dd440b8d3.png; x_0 + \gamma X \
Formula = 1045; 5/f/f/5ff443153b990aa41250fc4d2ac7b3b2.png; \frac{log|x|}{\pi} \

# References syntax format is "author1, author2,..., authorLast; year; title; journal; volume, number, pages; URL" 
[references] 
Ref = 1; Ivo D. Dinov, Nicolas Christou, Juana Sanchez; 2008; Central Limit Theorem: New SOCR Applet and Demonstration Activity; Journal of Statistics Education; Volume 16, Number 2; http://www.amstat.org/publications/jse/v16n2/dinov.html
Ref = 2; Leemis ML, McQueston JT; 2008; Univariate Distribution Relationships; Americal Statistician; 62(1), 45-53; http://www.ingentaconnect.com/content/asa/tas/2008/00000062/00000001/art00008
Ref = 3; Song, WT; 2005; Relationships Among Some Univariate Distributions; IIE Transaction; 37, 651-656; http://pdfserve.informaworld.com/316347_770849120_714035367.pdf
#T from Z and chi square
Ref = 4; Evans, M., Hastings, N., and Peacock, B.; 2000; Statistical Distributions (3rd ed.); Measurement Science and Technology; Volume 12, p.117; http://www.iop.org/EJ/abstract/0957-0233/12/1/702
#Beta Distribution from F
Ref = 5; Hogg, R.V., McKean, J.W., and Craig., A.T.; 2005; Introduction to Mathematical Statistics (6th ed.); journal; volume; http://math.bnu.edu.cn/~chj/lect-1.pdf
#Beta From Gamma
Ref = 6; Stacy, E.W.; 1962; A Generalization of the Gamma Distribution; Annals of Mathematical Statistics; 33, 1187-1192; http://www.projecteuclid.org/DPubS?verb=Display&version=1.0&service=UI&handle=euclid.aoms/1177704481&page=record
#Logarithmic
Ref = 7; Johnson, N.L., Kemp, A.W., and Kotz, S.; 2005; Univariate Discrete Distributions (3rd ed.); New York: Wiley.; Volume; http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470383372.html
#logistic-exponential distribution
Ref = 8; Lan, L., and Leemis, L. ;2007; The Logistic Exponential Survival Distributionl; Naval Research Logistics (NRL); Volume 55 Issue 3, Pages 252 - 264; http://www3.interscience.wiley.com/journal/117924447/abstract?CRETRY=1&SRETRY=0
#arctan distribution (glen and gleemis)
Ref = 9; Glen, A., and Leemis, L.M.; 1997; The Arctangent Survival Distributio; Journal of Quality Technology; 29, 205-210; http://www.asq.org/qic/display-item/index.html?item=11493
#Benford distribution 
Ref = 10; Benford, F. ;1938; The Law of Anomalous Numbers; Proceedings of the American Philosophical Society; 78(4), 551-572; http://www.jstor.org/pss/984802
#exponential power distribution (smith and Bain)
Ref = 11; Smith, R.M., and Bain, L.J.; 1975; An Exponential Power Life-Testing Distribution; Communications in Statistics - Simulation and Computation; Volume 4, Issue 5 1975 , pages 469 - 481; http://www.informaworld.com/smpp/content~content=a791522781~db=all 
#power distribution (balakrishnan and nevzorov)
Ref = 12; Balakrishnan, N., and Nevzorov, V.B.; 2003; A Primer on Statistical Distributions; Journal of the American Statistical Association; Volume 99, Number 466, 1 June 2004 , pp. 568-568(1); http://www.ingentaconnect.com/content/asa/jasa/2004/00000099/00000466/art00039



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