def dist(value):
return switch(
ge(value, 0) & gt(alpha, 0) & gt(beta, 0) & ge(n, value),
gammaln(alpha + beta) - gammaln(alpha) - gammaln(beta) +
gammaln(n + 1) - gammaln(value + 1) - gammaln(n - value + 1) +
gammaln(alpha + value) + gammaln(n + beta - value) -
gammaln(beta + alpha + n), -inf)
def dist(value):
return switch( gt(lam,0),
#factorial not implemented yet, so
value * log(lam) - gammaln(value + 1) - lam,
-inf)
def dist(value):
return switch(ge(value , 0) & gt(alpha , 0) & gt(beta , 0),
-gammaln(alpha) + alpha*log(beta) - beta*value + switch(alpha != 1.0, (alpha - 1.0)*log(value), 0),
-inf)
def dist(value):
return switch(gt(lam , 0) & gt(nu , 0),
gammaln((nu+1.0)/2.0) + .5 * log(lam / (nu * pi)) - gammaln(nu/2.0) - (nu+1.0)/2.0 * log(1.0 + lam *(value - mu)**2/nu),
-inf)
def dist(value):
return switch (ge(value , 0) & gt(alpha , 0) & gt(beta , 0) & ge(n , value),
gammaln(alpha+beta) - gammaln(alpha) - gammaln(beta)+ gammaln(n+1)- gammaln(value+1)- gammaln(n-value +1) + gammaln(alpha+value)+ gammaln(n+beta-value)- gammaln(beta+alpha+n),
-inf)
def dist(value):
return switch(ge(value , 0) & le(value , 1) &
gt(alpha , 0) & gt(beta , 0),
gammaln(alpha+beta) - gammaln(alpha) - gammaln(beta) + (alpha- 1)*log(value) + (beta-1)*log(1-value),
-inf)
def factln(n):
return gammaln(n + 1)
def dist(value):
return switch( gt(lam,0),
#factorial not implemented yet, so
value * log(lam) - gammaln(value + 1) - lam,
-inf)
def dist(value):
return switch(ge(value , 0) & gt(alpha , 0) & gt(beta , 0),
-gammaln(alpha) + alpha*log(beta) - beta*value + switch(alpha != 1.0, (alpha - 1.0)*log(value), 0),
-inf)
def dist(value):
return switch(gt(lam , 0) & gt(nu , 0),
gammaln((nu+1.0)/2.0) + .5 * log(lam / (nu * pi)) - gammaln(nu/2.0) - (nu+1.0)/2.0 * log(1.0 + lam *(value - mu)**2/nu),
-inf)
def dist(value):
return switch(ge(value , 0) & le(value , 1) &
gt(alpha , 0) & gt(beta , 0),
gammaln(alpha+beta) - gammaln(alpha) - gammaln(beta) + (alpha- 1)*log(value) + (beta-1)*log(1-value),
-inf)
def factln(n):
return gammaln(n + 1)
def Gamma(value, alpha, beta):
return switch((value >= 0) & (alpha > 0) & (beta > 0),
-gammaln(alpha) + alpha*log(beta) - beta*value + switch(alpha != 1.0, (alpha - 1.0)*log(value), 0),
-inf)
def T(value, mu, lam, nu):
return switch((lam > 0) & (nu > 0),
gammaln((nu+1.0)/2.0) + .5 * log(lam / (nu * pi)) - gammaln(nu/2.0) - (nu+1.0)/2.0 * log(1.0 + lam *(value - mu)**2/nu),
-inf)
def BetaBin(value, alpha, beta, n):
return switch ((value >= 0) & (alpha > 0) & (beta > 0) & (n >= value),
gammaln(alpha+beta) - gammaln(alpha) - gammaln(beta)+ gammaln(n+1)- gammaln(value+1)- gammaln(n-value +1) + gammaln(alpha+value)+ gammaln(n+beta-value)- gammaln(beta+alpha+n),
-inf)
def Beta(value, alpha, beta):
return switch((value >= 0) & (value <= 1) &
(alpha > 0) & (beta > 0),
gammaln(alpha+beta) - gammaln(alpha) - gammaln(beta) + (alpha- 1)*log(value) + (beta-1)*log(1-value),
-inf)