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prob [2012/11/16 12:08] – ignacyprob [2012/12/06 18:41] – ignacy
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-=====Module Prob===== +======Module Prob====== 
- +Ignacy Misztal and Deukhwan Lee, University of Georgia \\ 
- +04/29/99-04/19/2001 \\
- +
-  +
-Ignacy Misztal and Deukhwan Lee, University of Georgia +
-04/29/99-04/19/2001 +
- +
-=== Introduction === +
  
 Module Prob is a collection of random number generators / probabilities /  Module Prob is a collection of random number generators / probabilities / 
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 Module prob uses high-quality generators from public domain package RANLIB for Module prob uses high-quality generators from public domain package RANLIB for
-random number generators. Some low level code is from Luis Varona.+random number generators. Some low level code is from Luis Varona.\\
  
 +==== Subroutines/functions==== 
  
 +''call set_seed(n)'' \\
 +Sets seed for random number generator to integer n. If this subroutine is not
 +called, the seed will be selected by the system. \\
 +\\
  
-=== Module Prob === +''x=gen_uniform(a,b)''\\ 
- +a,b - both real (r*) or both integers or both missing.\\ 
- +If a,b are missing, generates samples from uniform(0,1) distribution. \\ 
-=== Set_seed === +If a,b are real (r8), generates samples from uniform(a,b) distribution. \\ 
- +If a,b are integers, generates random integer between a and b. \\ 
- +\\ 
-call set_seed(n) +  
- +''x=gen_normal(mean,var)''\\ 
-n - integer +mean - (r8) scalar or vector\\ 
- +var  - (r8) scalar or square matrix\\ 
-Sets seed for random number generator to value n. If this subroutine is not +x    - (r8) scalar or square matrix\\
-called, the seed will be selected by the system.  +
- +
- +
- +
-=== Gen_uniform === +
- +
- +
- +
-x=gen_uniform(a,b) +
- +
-a,b - both real (r*) or both integers or both missing +
- +
-If a,b are missing, generates samples from uniform(0,1) distribution.  +
- +
-If a,b are real (r8), generates samples from uniform(a,b) distribution.  +
- +
-If a,b are integers, generates random integer between a and b.  +
- +
- +
- +
-=== Gen_normal === +
- +
-x    - gen_normal(mean,var) +
- +
-mean - (r8) scalar or vector +
- +
-var  - (r8) scalar or square matrix +
- +
-x    - (r8) scalar or square matrix+
  
 Generates x=N(mean,Var) when mean and var are scalars, or  Generates x=N(mean,Var) when mean and var are scalars, or 
 x=MVN(mean,Var) when mean is a vector and Var is a matrix.  x=MVN(mean,Var) when mean is a vector and Var is a matrix. 
- 
 Arguments mean and var are optional. If they are missing, sampling is  Arguments mean and var are optional. If they are missing, sampling is 
-from N(0,1)+from N(0,1)\\ 
 +\\
  
  
-=== Gen_invwishart === +''x=gen_invwishart(inv_q_form,df)''
- +
- +
- +
- x=gen_invwishart(inv_q_form,df)+
    
-inv_q_form - (r8) scalar or square matrix containing inverse of quadratic form+inv_q_form - (r8) scalar or square matrix containing inverse of quadratic form\\ 
 +df         - an integer containing degrees of freedom\\
  
-df         - an integer containing degrees of freedom+Generates samples from inverted chi square or inverted Wishart distributions.\\ 
 +\\
  
 +''y=normal(x)''\\
 +x - real(r8) scalar\\
 +y  - real (r8) contains density(X) for N(0,1)\\
 +\\
  
-Generates samples from inverted chi square or inverted Wishart distributions. +''y=normal_cdf(x)''\\ 
- +x - real (r8) scalar\\ 
- +y - real (r8) cumulative distribution function for N(0,1)\\ 
- +\\
-=== Normal === +
- +
- +
-y=normal(x) +
- +
-x - real(r8) scalar +
- +
-y  - real (r8) contains density(X) for N(0,1) +
- +
- +
- +
-=== Normal_cdf === +
- +
- +
- +
-y=normal_cdf(x) +
- +
-x - real (r8) scalar +
- +
-y - real (r8) cumulative distribution function for N(0,1) +
- +
- +
- +
-=== Normal_invcdf === +
  
 y=normal_invcdf(x) y=normal_invcdf(x)
  
-x - real (r8) scalar in the range of <0,1>. +x - real (r8) scalar in the range of <0,1>\\ 
 +y - real (r8) as in: x=normal_cdf(y)\\ 
 +\\
  
-y - - real (r8) as in: x=normal_cdf(y)+''y=generate_trunc_normal(a,b,mean,var)''\\ 
 +y - real (r8) scalar or vector\\
  
 +a,b - real (r8) lower and upper bound of random samples\\
  
 +mean - real(r8) scalar or vectors of mean, optional if scalar\\
  
-=== Gen_trunc_normal === +var - real(r8) variance or covariance matrix, optional if scalar\\ 
- +\\
-y=generate_trunc_normal(a,b,mean,var) +
- +
-y - real (r8) scalar or vector +
- +
-a,b - real (r8) lower and upper bound of random samples +
- +
-mean - real(r8) scalar or vectors of mean, optional if scalar +
- +
-var - real(r8) scalar or matricex of variances, optional if scalar +
 If mean and var are missing, generates random samples from N(0,1) distribution  If mean and var are missing, generates random samples from N(0,1) distribution 
-truncated to interval <a,b>. +truncated to interval <a,b>.\\ 
 +\\
 If mean and var are scalars, generates random samples from N(mean,var)  If mean and var are scalars, generates random samples from N(mean,var) 
-distribution truncated to interval <a,b>.+distribution truncated to interval <a,b>.\\
  
 If mean is a vector and var is a matrix, generates random samples from  If mean is a vector and var is a matrix, generates random samples from 
-MVN(mean,var) distribution with first dimension truncated to interval <a,b>. +MVN(mean,var) distribution with first dimension truncated to interval <a,b>.\\ 
 +\\
  
 === Other functions/subroutines === === Other functions/subroutines ===
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prob.txt · Last modified: 2024/03/25 18:22 by 127.0.0.1
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