funsZmixed.nonref | R Documentation |
Two functions: Zmixed.nonref.ct
and Zmixed.nonref
.
Both functions are objects of class "htest"
but with different arguments (see the parameter list below).
Each one performs hypothesis tests of mixed non-reflexivity in the NN structure using the
number of mixed-non-reflexive NN pairs (i.e. the second diagonal entry, (2,2)) in the RCT for k ≥ 2 classes.
That is, each test performs a test of mixed non-reflexivity corresponding to entry (2,2) in the RCT)
which is appropriate (i.e. have the appropriate asymptotic sampling distribution) for completely mapped data.
(See \insertCiteceyhan:NNreflexivity2017;textualnnspat for more detail).
The mixed non-reflexivity test is based on the normal approximation of the diagonal entry (2,2) in the RCT and are due to \insertCiteceyhan:NNreflexivity2017;textualnnspat.
Each function yields the test statistic, p-value for the corresponding alternative, the confidence interval, sample estimate (i.e. observed value) and null (i.e., expected) value for the mixed non-reflexivity value (i.e., diagonal entry (2,2) value, respectively) in the RCT, and method and name of the data set used.
The null hypothesis is that E(N_{22})=R P_{ab} in the RCT, where R is the number of reflexive NNs and P_{ab} is the probability of any two points selected are being from two different classes.
Zmixed.nonref.ct( rfct, nvec, Qv, Tv, alternative = c("two.sided", "less", "greater"), conf.level = 0.95 ) Zmixed.nonref( dat, lab, alternative = c("two.sided", "less", "greater"), conf.level = 0.95, ... )
rfct |
An RCT, used in |
nvec |
The |
Qv |
The number of shared NNs, used in |
Tv |
T value, which is the number of triplets (z_i, z_j, z_k) with
"NN(z_i) = NN(z_j) = z_k and NN(z_k) = z_j where NN(\cdot) is the nearest neighbor function, used in |
alternative |
Type of the alternative hypothesis in the test, one of |
conf.level |
Level of the upper and lower confidence limits, default is |
dat |
The data set in one or higher dimensions, each row corresponds to a data point,
used in |
lab |
The |
... |
are for further arguments, such as |
A list
with the elements
statistic |
The Z test statistic for mixed non-reflexivity corresponding to entry (2,2) in the RCT |
p.value |
The p-value for the hypothesis test for the corresponding alternative |
conf.int |
Confidence interval for the mixed non-reflexivity value (i.e., diagonal entry (2,2) value)
in the RCT at the given confidence level |
estimate |
Estimate of the parameter, i.e., the observed diagonal entry (2,2) in the RCT, |
null.value |
Hypothesized null value for the mixed non-reflexivity value (i.e., expected value of the diagonal entry (2,2) which is E(N_{22})=R P_{ab}) in the RCT. |
alternative |
Type of the alternative hypothesis in the test, one of |
method |
Description of the hypothesis test |
ct.name |
Name of the contingency table, |
data.name |
Name of the data set, |
Elvan Ceyhan
Zself.ref.ct
, Zself.ref
, Znnref.ct
and
Znnref
n<-20 Y<-matrix(runif(3*n),ncol=3) cls<-sample(1:2,n,replace = TRUE) #or try cls<-rep(1:2,c(10,10)) ipd<-ipd.mat(Y) W<-Wmat(ipd) Qv<-Qvec(W)$q R<-Rval(W) Tv<-Tval(W,R) nvec<-as.numeric(table(cls)) rfct<-rct(ipd,cls) Zmixed.nonref(Y,cls) Zmixed.nonref.ct(rfct,nvec,Qv,Tv) Zmixed.nonref(Y,cls,alt="g") Zmixed.nonref(Y,cls,method="max") ############# n<-40 Y<-matrix(runif(3*n),ncol=3) cls<-sample(1:4,n,replace = TRUE) #or try cls<-rep(1:2,c(10,10)) ipd<-ipd.mat(Y) W<-Wmat(ipd) Qv<-Qvec(W)$q R<-Rval(W) Tv<-Tval(W,R) nvec<-as.numeric(table(cls)) rfct<-rct(ipd,cls) Zmixed.nonref(Y,cls,alt="g") Zmixed.nonref.ct(rfct,nvec,Qv,Tv) Zmixed.nonref.ct(rfct,nvec,Qv,Tv,alt="l")
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