Probability Distribution and Statistical Functions -- Exponential Distribution Module

doc/specs/index.md

@@ -29,6 +29,7 @@ This is and index/directory of the specifications (specs) for each new module/fe
  - [stats](./stdlib_stats.html) - Descriptive Statistics
  - [stats_distributions_uniform](./stdlib_stats_distribution_uniform.html) - Uniform Probability Distribution
  - [stats_distributions_normal](./stdlib_stats_distribution_normal.html) - Normal Probability Distribution
+ - [stats_distributions_exponential](./stdlib_stats_distribution_exponential.html) - Exponential Probability Distribution
  - [string\_type](./stdlib_string_type.html) - Basic string support
  - [strings](./stdlib_strings.html) - String handling and manipulation routines
  - [stringlist_type](./stdlib_stringlist_type.html) - 1-Dimensional list of strings

doc/specs/stdlib_stats_distribution_exponential.md

@@ -0,0 +1,248 @@
+---
+title: stats_distribution_exponential
+---
+
+# Statistical Distributions -- Exponential Distribution Module
+
+[TOC]
+
+## `rvs_exp` - exponential distribution random variates
+
+### Status
+
+Experimental
+
+### Description
+
+An exponential distribution is the distribution of time between events in a Poisson point process. The inverse scale parameter `lambda` specifies the average time between events, also called the rate of events.
+
+Without argument the function returns a random sample from the standard exponential distribution `E(1)` with `lambda = 1`.
+
+With a single argument, the function returns a random sample from the exponential distribution `E(lambda)`.
+For complex arguments, the real and imaginary parts are sampled independently of each other.
+
+With two arguments the function returns a rank one array of exponentially distributed random variates.
+
+Note: the algorithm used for generating exponetial random variates is fundamentally limited to double precision. Ref.: Marsaglia, G. & Tsang, W.W. (2000) `The ziggurat method for generating random variables', J. Statist. Software, v5(8).
+
+### Syntax
+
+`result = [[stdlib_stats_distribution_exponential(module):rvs_exp(interface)]]([lambda] [[, array_size]])`
+
+### Class
+
+Function
+
+### Arguments
+
+`lambda`: optional argument has `intent(in)` and is a scalar of type `real` or `complex`. The value of `lambda` has to be non-negative.
+
+`array_size`: optional argument has `intent(in)` and is a scalar of type `integer` with default kind.
+
+### Return value
+
+The result is a scalar or rank one array with a size of `array_size`, and has the same type of `lambda`.
+
+### Example
+
+```fortran
+program demo_exponential_rvs
+    use stdlib_random, only : random_seed
+    use stdlib_stats_distribution_exponential, only: rexp => rvs_exp
+
+    implicit none
+    real ::  a(2,3,4)
+    complex :: scale
+    integer :: seed_put, seed_get
+
+    seed_put = 1234567
+    call random_seed(seed_put, seed_get)
+
+    print *, rexp( )         !single standard exponential random variate
+
+! 0.358690143
+
+    print *, rexp(2.0)       !exponential random variate with lambda=2.0
+
+! 0.816459715
+
+    print *, rexp(0.3, 10)   !an array of 10 variates with lambda=0.3
+
+!  1.84008647E-02  3.59742008E-02  0.136567295  0.262772143  3.62352766E-02 
+!  0.547133625  0.213591918  4.10784185E-02  0.583882213  0.671128035
+
+    scale = (2.0, 0.7)
+    print *, rexp(scale)
+    !single complex exponential random variate with real part of lambda=2.0;
+    !imagainary part of lambda=0.7
+
+! (1.41435969,4.081114382E-02)
+
+end program demo_exponential_rvs
+```
+
+## `pdf_exp` - exponential distribution probability density function
+
+### Status
+
+Experimental
+
+### Description
+
+The probability density function (pdf) of the single real variable exponential distribution:
+
+$$f(x)=\begin{cases} \lambda e^{-\lambda x} &x\geqslant 0 \\\\ 0 &x< 0\end{}$$
+
+For a complex variable (x + y i) with independent real x and imaginary y parts, the joint probability density function
+is the product of the corresponding marginal pdf of real and imaginary pdf (for more details, see
+"Probability and Random Processes with Applications to Signal Processing and Communications", 2nd ed., Scott L. Miller and Donald Childers, 2012, p.197):
+
+$$f(x+\mathit{i}y)=f(x)f(y)=\begin{cases} \lambda_{x} \lambda_{y} e^{-(\lambda_{x} x + \lambda_{y} y)} &x\geqslant 0, y\geqslant 0 \\\\ 0 &otherwise\end{}$$
+
+### Syntax
+
+`result = [[stdlib_stats_distribution_exponential(module):pdf_exp(interface)]](x, lambda)`
+
+### Class
+
+Elemental function
+
+### Arguments
+
+`x`: has `intent(in)` and is a scalar of type `real` or `complex`.
+
+`lambda`: has `intent(in)` and is a scalar of type `real` or `complex`.
+
+All arguments must have the same type.
+
+### Return value
+
+The result is a scalar or an array, with a shape conformable to arguments, and has the same type of input arguments.
+
+### Example
+
+```fortran
+program demo_exponential_pdf
+    use stdlib_random, only : random_seed
+    use stdlib_stats_distribution_exponential, only: exp_pdf => pdf_exp,     &
+                                                     rexp => rvs_exp
+
+    implicit none
+    real :: x(2,3,4),a(2,3,4)
+    complex :: scale
+    integer :: seed_put, seed_get
+
+    seed_put = 1234567
+    call random_seed(seed_put, seed_get)
+
+    print *, exp_pdf(1.0,1.0) !a probability density at 1.0 in standard expon
+
+! 0.367879450
+
+    print *, exp_pdf(2.0,2.0) !a probability density at 2.0 with lambda=2.0
+
+! 3.66312787E-02
+
+    x = reshape(rexp(0.5, 24),[2,3,4]) ! standard expon random variates array
+    a(:,:,:) = 0.5
+    print *, exp_pdf(x, a)     ! a rank 3 standard expon probability density
+
+!  0.457115263  0.451488823  0.492391467  0.485233188  0.446215510 
+!  0.401670188  0.485127628  0.316924453  0.418474048  0.483173639 
+!  0.307366133  0.285812140  0.448017836  0.426440030  0.403896868 
+!  0.334653258  0.410376132  0.485370994  0.333617479  0.263791025 
+!  0.249779820  0.457159877  0.495636940  0.482243657
+
+    scale = (1.0, 2.)
+    print *, exp_pdf((1.5,1.0), scale)
+    ! a complex expon probability density function at (1.5,1.0) with real part
+    !of lambda=1.0 and imaginary part of lambda=2.0
+
+! 6.03947677E-02
+
+end program demo_exponential_pdf
+```
+
+## `cdf_exp` - exponential cumulative distribution function
+
+### Status
+
+Experimental
+
+### Description
+
+Cumulative distribution function (cdf) of the single real variable exponential distribution:
+
+$$F(x)=\begin{cases}1 - e^{-\lambda x} &x\geqslant 0 \\\\ 0 &x< 0\end{}$$
+
+For a complex variable (x + y i) with independent real x and imaginary y parts, the joint cumulative distribution
+function is the product of corresponding marginal cdf of real and imaginary cdf (for more details, see
+"Probability and Random Processes with Applications to Signal Processing and Communications", 2nd ed., Scott L. Miller and Donald Childers, 2012, p.197):
+
+$$F(x+\mathit{i}y)=F(x)F(y)=\begin{cases} (1 - e^{-\lambda_{x} x})(1 - e^{-\lambda_{y} y}) &x\geqslant 0, \;\; y\geqslant 0 \\\\ 0 &otherwise \end{}$$
+
+### Syntax
+
+`result = [[stdlib_stats_distribution_exponential(module):cdf_exp(interface)]](x, lambda)`
+
+### Class
+
+Elemental function
+
+### Arguments
+
+`x`: has `intent(in)` and is a scalar of type `real` or `complex`.
+
+`lambda`: has `intent(in)` and is a scalar of type `real` or `complex`.
+
+All arguments must have the same type.
+
+### Return value
+
+The result is a scalar or an array, with a shape conformable to arguments, and has the same type of input arguments.
+
+### Example
+
+```fortran
+program demo_exponential_cdf
+    use stdlib_random, only : random_seed
+    use stdlib_stats_distribution_exponential, only : exp_cdf => cdf_exp,    &
+                                                      rexp => rvs_exp
+
+    implicit none
+    real :: x(2,3,4),a(2,3,4)
+    complex :: scale
+    integer :: seed_put, seed_get
+
+    seed_put = 1234567
+    call random_seed(seed_put, seed_get)
+
+    print *, exp_cdf(1.0, 1.0)  ! a standard exponential cumulative at 1.0
+
+! 0.632120550
+
+    print *, exp_cdf(2.0, 2.0) ! a cumulative at 2.0 with lambda=2
+
+! 0.981684387
+
+    x = reshape(rexp(0.5, 24),[2,3,4])
+    ! standard exponential random variates array
+    a(:,:,:) = 0.5
+    print *, exp_cdf(x, a)  ! a rank 3 array of standard exponential cumulative
+
+!  8.57694745E-02  9.70223546E-02  1.52170658E-02  2.95336246E-02 
+!  0.107568979  0.196659625  2.97447443E-02  0.366151094  0.163051903 
+!  3.36527228E-02  0.385267735  0.428375721  0.103964329  0.147119939 
+!  0.192206264  0.330693483  0.179247737  2.92580128E-02  0.332765043 
+!  0.472417951  0.500440359  8.56802464E-02  8.72612000E-03  3.55126858E-02
+
+    scale = (0.5,1.0)
+    print *, exp_cdf((0.5,0.5),scale)
+    !complex exponential cumulative distribution at (0.5,0.5) with real part of
+    !lambda=0.5 and imaginary part of lambda=1.0
+
+! 8.70351046E-02
+
+end program demo_exponential_cdf
+
+```

src/CMakeLists.txt

@@ -39,6 +39,7 @@ set(fppFiles
     stdlib_stats_moment_scalar.fypp
     stdlib_stats_distribution_uniform.fypp
     stdlib_stats_distribution_normal.fypp
+    stdlib_stats_distribution_exponential.fypp
     stdlib_stats_var.fypp
     stdlib_quadrature.fypp
     stdlib_quadrature_trapz.fypp

src/Makefile.manual

@@ -41,6 +41,7 @@ SRCFYPP = \
         stdlib_stats_moment_scalar.fypp \
         stdlib_stats_distribution_uniform.fypp \
         stdlib_stats_distribution_normal.fypp \
+        stdlib_stats_distribution_exponential.fypp \
         stdlib_stats_var.fypp \
         stdlib_math.fypp \
         stdlib_math_linspace.fypp \
@@ -203,6 +204,11 @@ stdlib_stats_distribution_normal.o: \
     stdlib_error.o \
     stdlib_random.o \
     stdlib_stats_distribution_uniform.o
+stdlib_stats_distribution_exponential.o: \
+    stdlib_kinds.o \
+    stdlib_error.o \
+    stdlib_random.o \
+    stdlib_stats_distribution_uniform.o
 stdlib_random.o: \
     stdlib_kinds.o \
     stdlib_error.o