View source: R/225.CoverageProb_GENERAL_SIMULATEDp.R
covpSIM | R Documentation |
Coverage Probability using simulation Coverage probability for CI obtained from any method over the space [0, 1]
covpSIM(n, LL, UL, alp, s, a, b, t1, t2)
n |
- Number of trials |
LL |
- Lower limit |
UL |
- Upper limit |
alp |
- Alpha value (significance level required) |
s |
- Number of hypothetical "p" |
a |
- Beta parameters for hypo "p" |
b |
- Beta parameters for hypo "p" |
t1 |
- Lower tolerance limit to check the spread of coverage Probability |
t2 |
- Upper tolerance limit to check the spread of coverage Probability |
Evaluation of intervals obtained from any method using coverage probability,
root mean square statistic, and the proportion of proportion lies within the desired
level of coverage for the n + 1 intervals and pre-defined space for the parameter
p
using Monte Carle simulation
A dataframe with
mcp |
Mean Coverage Probability |
micp |
Minimum coverage probability |
RMSE_N |
Root Mean Square Error from nominal size |
RMSE_M |
Root Mean Square Error for Mean Coverage Probability |
RMSE_MI |
Root Mean Square Error for minimum coverage probability |
tol |
Required tolerance for coverage probability |
Other Simulated methods for coverage probability:
PlotcovpSIM()
LL=c(0,0.01,0.0734,0.18237,0.3344,0.5492) #Lower and Upper Limits UL=c(0.4507,0.6655,0.8176,0.9265,0.9899,1) n= 5; alp=0.05; s=5000; a=1; b=1; t1=0.93; t2=0.97 covpSIM(n,LL,UL,alp,s,a,b,t1,t2)
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