[General]
network = Dist

Dist.n = 200000
Dist.discrete = false  # default for the cont. distrs.
Dist.numcells = 100
Dist.firstvals = 100
Dist.file = "" # automatic filename
Dist.excel = "0"  # default (used where excel has no pdf)

#----------------------------------------------------------------------
# CONTINUOUS
#----------------------------------------------------------------------

#
# uniform :)
#
[Config uniform1]
Dist.variate = uniform(0,1)
Dist.excel = "1"
# -->OK

[Config uniform2]
Dist.variate = uniform(-3,7)
Dist.excel = "0.1"
# -->OK

#
# normal, truncnormal
#
[Config normal1]
Dist.variate = normal(0,1)
Dist.excel = "NORMDIST(A%d,0,1,0)"
# -->OK

[Config normal2]
Dist.variate = normal(5,3)
Dist.excel = "NORMDIST(A%d,5,3,0)"
# -->OK

[Config truncnormal]
Dist.variate = truncnormal(${a=0,-1},${b=1,4})
Dist.excel = "IF(NORMDIST(A%d,${a},${b},0)<0,0,NORMDIST(A%d,${a},${b},0)/(1-NORMDIST(0,0,1,1)))"
# -->OK


#
# exponential
#
[Config exponential]
Dist.variate = exponential(3)
Dist.excel = "EXPONDIST(A%d,1/3,0)"
# -->OK


#
# gamma
#
[Config gamma]
Dist.variate = gamma_d(${a=0.01,0.1,0.6,0.95,1,1.05,2,7},${b=2,5})
Dist.excel = "GAMMADIST(A%d,${a},${b},0)"
# -->OK (since alpha=1, this is exponential distribution)

#
# erlang
#
# erlang(k,m) == gamma(k,m/k)
#
[Config erlang]
Dist.variate = erlang_k(${a=1,5,10},${b=1,100,10,0.5})
Dist.excel = "GAMMADIST(A%d,${a},${b},0)"
# -->OK

#
# triang
#
[Config triang1]
Dist.variate = triang(0,0.3,1)
# -->OK

[Config triang2]
Dist.variate = triang(0,0,1)
# -->OK

[Config triang3]
Dist.variate = triang(0,1,1)
# -->OK

[Config triang4]
Dist.variate = triang(-1,4,5)
# -->OK


#
# lognormal
#
# no lognormal pdf in Excel.
# f(X)=exp(-1/2*((ln(X)-m)/s)^2) / sqrt(2*PI()*s^2*X^2)   (source: xycoon.com)
#
[Config lognormal]
Dist.variate = lognormal(${m=0,1},${w=0.1,0.5,0.7,1})
Dist.excel = "exp(-1/2*((ln(A%d)-${m})/${w})^2) / sqrt(2*PI()*${w}^2*A%d^2)"
# -->OK

#
# Weibull
#
# Excel's (alpha,beta) parameters correspond to our (b,a) (swapped!)
#
[Config weibull]
Dist.variate = weibull(${a=1,2,5},${b=1,2,5})
Dist.excel = "WEIBULL(A%d,${a},${b},0)"
# -->OK


#
# beta
#
[Config beta]
Dist.variate = beta(${a=0.5,0.75,1,2,4,10,25},${b=0.75,1,2,4,10})
# -->OK

#
# chi-squared
#
# excel's CHIDIST is surely wrong: different shape, and in any case
# it doesn't integrate to 1. we use GAMMADIST for testing instead:
#
# chi-square(k) = gamma(k/2,2)
#
[Config chi_square]
Dist.variate = chi_square(${a=1,2,5,10,25,50})
Dist.excel = "GAMMADIST(A%d,${a}/2,2,0)"
# -->OK

#
# student-t
#
# note: excel is wrong here, TDIST always creates 2-tailed distrib,
# regardless of its "tails" parameter, and also it seemingly doesn't
# integrate to 1!
#
# visual inspection was used, and compared to graphs at www.xycoon.com
#
[Config student_t]
Dist.variate = student_t(${a=1,2,5,30,100})
# -->seems OK

#
# cauchy
#
# excel has no cauchy pdf.
# f(X)=b/PI/((X-a)^2+b^2)  (source: xycoon.com)
#
# firstvals had to be decreased, otherwise a few very high values (>1000)
# occur and spoil the histogram range
#
[Config cauchy]
Dist.variate = cauchy(${a=0,5},${b=1,3})
Dist.excel = "${b}/PI()/((A%d-${a})^2+${b}^2)"
Dist.firstvals = 15
# -->OK

#
# pareto
#
# excel has no pareto pdf.
# f(X)=a/b*(b/(X+c))^(a+1)  (source: xycoon.com)
#
# firstvals had to be decreased, otherwise a few very high values (>100)
# occur and spoil the histogram range
#
[Config pareto]
Dist.variate = pareto_shifted(${a=1,5,10},${b=1,5,10},${c=0,8})
Dist.excel = "${a}/${b}*(${b}/(A%d+${c}))^(${a}+1)"
Dist.firstvals = 15
# -->OK

#----------------------------------------------------------------------
# DISCRETE
#----------------------------------------------------------------------

#
# intuniform
#
[Config intuniform]
Dist.variate = intuniform(0,9)
Dist.excel = "0.1"
Dist.discrete = true
Dist.numcells = 12
# -->OK

#
# bernoulli
#
[Config bernoulli]
Dist.variate = bernoulli(0.2)
Dist.excel = "if(A%=0,0.2,0.8)"
Dist.discrete = true
Dist.numcells = 2
# -->OK

#
# binomial
#
[Config binomial]
Dist.variate = binomial(${a=1,10}, ${b=0,0.2,1})
Dist.excel = "BINOMDIST(A%d,${a},${b},0)"
Dist.discrete = true
Dist.numcells = 5
# -->OK

#
# geometric
#
[Config geometric]
Dist.variate = geometric(${a=0.2,0.8,2})
Dist.excel = "NEGBINOMDIST(A%d,1,${a})"
Dist.discrete = true
Dist.numcells = 20
# -->OK


#
# negbinomial
#
[Config negbinomial]
Dist.variate = negbinomial(5,0.2)
Dist.excel = "NEGBINOMDIST(A%d,5,0.2)"
Dist.discrete = true
Dist.numcells = 20
# -->OK

#
# hypergeometric
#
# excel has different parameters: if we have (a,b,n), it expects (n,a,a+b)
#
# here we cannot test because hypergeometric is broken!
#
#Dist.variate=hypergeometric(5,5,1)
#Dist.excel="HYPGEOMDIST(A%d,1,5,10)"
#Dist.discrete=true
#Dist.numcells=10

#Dist.variate=hypergeometric(5,5,2)
#Dist.excel="HYPGEOMDIST(A%d,2,5,10)"
#Dist.discrete=true
#Dist.numcells=10

#Dist.variate=hypergeometric(0,10,1)
#Dist.excel="HYPGEOMDIST(A%d,1,0,10)"
#Dist.discrete=true
#Dist.numcells=10

#
# poisson
#
# we use different algorithms under 30 and above 30
#

[Config poisson]
Dist.variate = poisson(${a=5,29,31,50})
Dist.excel = "POISSON(A%d,$a{},0)"
Dist.discrete = true
Dist.numcells = 50
# -->OK

# -->similar but slight MISMATCH: POISSON's peak is 0.07, ours is 0.08
# -->similar but slight MISMATCH: POISSON's peak is 0.056, ours is 0.063