Sir,
I want to solve the equation Q(u)=mean, where Q(u) represents the quantile
function. Here my Q(u)=(c*u^lamda1)/((1-u)^lamda2), which is the quantile
function of Davies (Power-pareto) distribution. Hence I want to solve ,
*(c*u^lamda1)/((1-u)^lamda2)=28353.7(Eq.1)*
where lamda1=0.03399381,
Sir,
I want to write a loop in R to find the AIC factor. For its calculation, I
need to run an algorithm in the attached file. Here 'x' represents the
dataset and xi denotes the i-th observation after arranging it in ascending
order. Q(u) and q(u) represent the quantile function and quantile densi
How to calculate AIC , when the distribution have only quantile function
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the po
In my work, I use l-moments for estimation and obtain a system of
nonlinear equations. I am using the 'nleqslv' package in the R- program to
solve these equations but am struggling to choose initial values. Is there
any criteria to choose initial values in this package or is there any other
method
4 matches
Mail list logo