Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Kamal C. Chanda"'
Autor:
Kamal C. Chanda
Publikováno v:
Annals of the Institute of Statistical Mathematics. 58:635-646
We consider the sampling properties of U-statistics based on a sample of realization from a class of stationary nonlinear processes which include, in particular, linear, bilinear and finite order volterra processes. It is shown that if the size n of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf81d9c044c0f1ae09bab41ce5f22dad
https://doi.org/10.1007/s10463-006-0030-3
https://doi.org/10.1007/s10463-006-0030-3
Autor:
Kamal C. Chanda
Publikováno v:
Journal of Time Series Analysis. 26:1-16
We consider the standard spectral estimators based on a sample from a class of strictly stationary nonlinear processes which include, in particular, the bilinear and Volterra processes. It is shown that these estimators, under certain mild regularity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05be609020de23c03b3b5a3657418aa1
https://doi.org/10.1111/j.1467-9892.2005.00387.x
https://doi.org/10.1111/j.1467-9892.2005.00387.x
Autor:
Kamal C. Chanda
Publikováno v:
Annals of the Institute of Statistical Mathematics. 55:69-82
Let {X t ;t∈ℤ be a strictly stationary nonlinear process of the formX t =e t +∑ r=1 ∞ W rt , whereW rt can be written as a functiong r (e t−1,...e t-r-q ), {e t ;t∈ℤ is a sequence of independent and identically distributed (i.i.d.) rand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::674b2bedb8c8861e2da95b26b9a7ee96
https://doi.org/10.1007/bf02530485
https://doi.org/10.1007/bf02530485
Autor:
Kamal C. Chanda, Roger Barnard
Publikováno v:
Journal of Time Series Analysis. 16:445-449
Standard least squares analysis of autoregressive moving-average (ARMA) processes with errors-in-variables entails the construction of a new set of parameters which are functions of the original ARMA parameters, and requires that derivatives of these
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::90dca5edc4f4b8a78061ca5b372e2faa
https://doi.org/10.1111/j.1467-9892.1995.tb00245.x
https://doi.org/10.1111/j.1467-9892.1995.tb00245.x
Autor:
Kamal C. Chanda
Publikováno v:
Journal of Time Series Analysis. 16:1-15
We consider estimation of parameters of an unobservable ARMA(p, q) process {Ut; t= 1,2,…} based on a set of n observables, X1, …, Xn, where Xt=Ut, +et, 1 ≤t≤n, it being assumed that {et} is independent of {Ut}. We examine the asymptotic prope
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::24c8e6404150f398c12595f888e2a676
https://doi.org/10.1111/j.1467-9892.1995.tb00220.x
https://doi.org/10.1111/j.1467-9892.1995.tb00220.x
Autor:
Kamal C. Chanda
Publikováno v:
Journal of Multivariate Analysis. 47:163-171
Let {Xt; t ∈ Z} be a strictly stationary process with mean zero and autovariance function (a.c.v.f.) γv, v ∈ Z. Let γ̂v = n − 1 ∑n − |v|t = 1 be the serial covariance of order v computed from a sample X1, ..., Xn drawn from {Xt}. We assu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f4a24007a8814ff47130723bda8dd8b
https://doi.org/10.1006/jmva.1993.1077
https://doi.org/10.1006/jmva.1993.1077
Autor:
Kamal C. Chanda
Publikováno v:
Statistics & Probability Letters. 14:175-178
Let X1,…,Xn be a random sample from a distribution function (d.f.) F. Let Vn = Xkn:n be the intermediate knth order statistic for the random sample with kn→∞, but kn/n → 0 as n → ∞. A Bahadur—Kiefer type representation for Vn is establi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::200f2b3a0bb5fcae2a566cd62d8191fb
https://doi.org/10.1016/0167-7152(92)90018-z
https://doi.org/10.1016/0167-7152(92)90018-z
Autor:
Frits H. Ruymgaart, Kamal C. Chanda
Publikováno v:
Communications in Statistics - Theory and Methods. 21:3247-3254
In this note we derive asymptotic normality for a class of linear combinations of functions of concomitant order statistics by exploiting the relation between these statistics and rank statistics for testing independence. The proof can at once be obt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9399125bc9baa6a3f954028de28b549b
https://doi.org/10.1080/03610929208830975
https://doi.org/10.1080/03610929208830975
Autor:
Kamal C. Chanda
Publikováno v:
Journal of Time Series Analysis. 12:301-313
Consider the general bilinear times series model where {Xt; t= 0, L1, …} is a p-variate process, C(p x (s+ 1)), A(p x p). Bt(p x p) (1 ≤j≤q) are arbitrary matrices of constants, eT=[et,…et-q+1] and {et; t=0, ±1, …} is a strictly stationary
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::43735ad43138e42d18c3d4ba449b29ba
https://doi.org/10.1111/j.1467-9892.1991.tb00085.x
https://doi.org/10.1111/j.1467-9892.1991.tb00085.x
Publikováno v:
Journal of Multivariate Analysis. 35:260-275
In this paper we introduce the concept of m(n)-decomposability as an alternative to classical mixing concepts. We illustrate how to handle the ensuing technicalities by proving asymptotic normality of L-statistics, based on such a decomposable time s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fa2432e8ad124e777a00d50ef129c0f
https://doi.org/10.1016/0047-259x(90)90028-g
https://doi.org/10.1016/0047-259x(90)90028-g