| nsf, Tm, CparamCalculation, power.matrix, base, SmoothedEstimate {NPHazardRate} | R Documentation |
Auxiliary functions for discrete hazard rate estimators
Description
Auxiliary functions for discrete semiparametric and kernel smooth hazard rate estimation
Usage
nsf(xin, cens, xout)
Tm(tk, xout, distribution, par1, par2)
CparamCalculation(gamparam, VehHazard)
power.matrix(M, n)
base(m, b)
SmoothedEstimate(NonParEst, VehHazard, gammapar, SCproduct, Cpar)
Arguments
xin |
A vector of data points. Missing values not allowed. |
cens |
A vector of 1s and zeros, 1's indicate uncensored observations, 0's correspond to censored obs. |
xout |
The points where the estimate should be calculated. |
tk |
desing points for the NPMLE estimate. |
distribution |
which distribution to use? |
par1 |
distribution parameter 1 |
par2 |
distribution parameter 2 |
gamparam |
gamma parameter |
M |
a matrix to be raised to a power |
n |
the power the matrix will be raised at |
m |
express m as a power of b |
b |
express m as a power of b |
NonParEst |
The crude nonparametric hazard rate estimate. |
VehHazard |
Vehicle hazard rate |
gammapar |
gamma parameter |
SCproduct |
SC product, the result of DetermineSCprod |
Cpar |
C parameter, the result of CparamCalculation. |
Details
Auxiliary functions for discrete hazard rate estimators. The function nsf is used for the kernel smooth estimate TutzPritscher.
Tm used to calculate
\max(t_k; 1-\sum_{l=0}^k \eta_l > \epsilon), \epsilon>0in the implementation of the semiparametric estimateCparamCalculationreturns the C smoothing parameter calculated as
C= \gamma/\max_{k \geq 0} ( \lambda(t_{k-1}) + \lambda(t_k) + \lambda(t_{k+1}) )DetermineSCprodthis finds
SC = \gamma((n+1) \hat B_1)^{-1} \hat V_1n = number of obs, gammapar = sum of vehicle haz at xout (computed elsewhere)
Value
A vector with the values of the hazard rate estimates.