Lines Matching refs:mu
66 For mean parameters [mu] and scale (also called precision) parameter [lambda],
70 [expression f(x;[mu], [lambda]) = [sqrt]([lambda]/2[pi]x[super 3]) e[super -[lambda](x-[mu])[sup2]/…
74 [expression F(x;[mu], [lambda]) = [Phi]{[sqrt]([lambda]/x) (x/[mu]-1)} + e[super 2[mu]/[lambda]] […
79 varies for a few values of parameters [mu] and [lambda]:
85 Tweedie also provided 3 other parameterisations where ([mu] and [lambda])
86 are replaced by their ratio [phi] = [lambda]/[mu] and by 1/[mu]:
89 Another related parameterisation, the __wald_distrib (where mean [mu] is unity) is also provided.
95 Constructs an inverse_gaussian distribution with [mu] mean,
98 Requires that both the mean [mu] parameter and scale [lambda] are greater than zero,
103 Returns the mean [mu] parameter of this distribution.
128 In the following table [mu] is the mean parameter and
131 Parameters [mu] for shape and [lambda] for scale
136 [[pdf] [ [sqrt]([lambda]/ 2[pi]x[super 3]) e[super -[lambda](x - [mu])[sup2]/ 2[mu][sup2]x]]]
137 [[cdf][ [Phi]{[sqrt]([lambda]/x) (x/[mu]-1)} + e[super 2[mu]/[lambda]] [Phi]{-[sqrt]([lambda]/[mu])…
141 [[mode][[mu] {[sqrt](1+9[mu][sup2]/4[lambda][sup2])[sup2] - 3[mu]/2[lambda]} ]]
143 [[mean][[mu]] ]
144 [[variance][[mu][cubed]/[lambda]] ]
145 [[skewness][3 [sqrt] ([mu]/[lambda])] ]
146 [[kurtosis_excess][15[mu]/[lambda]] ]
147 [[kurtosis][12[mu]/[lambda]] ]