Nonparametric Change-Point Estimation

By Edward Carlstein. 1988

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Citations in the corpus

Differentially Private Change-Point Detection (2018, background): “The existing change-point literature works primarily in the asymptotic setting when k ∗ n /n → r for some r ∈ (0 , 1) as n → ∞ (see, e.g., [Hin70, Car88]).”
Empirical likelihood ratio test for the change-point problem (2007, background): “Nonparametric change-point problem also has extensive literature, such as Dumbgen (1991), Carlstein (1988), Pettitt (1979) and Yao (1990), and thorough discussions are given by Brodsky and Darkhovsky (1993) and also again Csorgo and Horvath (1997).”
Finite sample change point inference and identification for high‐dimensional mean vectors (2017, methodology): “Change point testing and estimation have a long history [45, 46, 41, 16, 31, 49, 10, 20, 33, 6, 23, 13, 37, 29, 27, 22, 24, 40, 3, 4, 7, 51, 30] and there are two major lines of change point tests in literature: sequential tests and fixed sample size tests [34].”
TESTING FOR DISTRIBUTIONAL CHANGE IN TIME SERIES (2001, methodology): “…function~m0n!~1 2 m0n! guarantees that the limiting distributions are well defined and has been used in the literature~se Deshayes and Picard, 1986; Carlstein, 1988; Bai, 1996!+ To study the limiting distributions ofT1 andT2, we introduce the following assumptions+ First, we need to restrict the…”
Detecting relevant changes in time series models (2014, methodology): “An estimator of the change-point can be obtained by the argmax-principle, that is t̂ = argmaxs∈[0,1]‖Ûn(s)‖ [see Carlstein (1988)].”
Detecting gradual changes in locally stationary processes (2013, background): “int between the segments is a well studied problem which has been analyzed in a variety of settings; see for example Hinkley [14], Worsley [29] and 1 arXiv:1310.4678v1 [stat.ME] 17 Oct 2013 Carlstein [3] among many others. The change point framework is apt to model abrupt changes over time. However,”
Testing relevant hypotheses in functional time series via self‐normalization (2018, background): “First, we note that there exists a general and well-developed machinery for establishing convergence rates of change point estimators [see, for example Carlstein (1988), Dümbgen (1991) or Hariz et al.”
Changepoints in the North Atlantic Tropical Cyclone Record (2011, unknown): “Other authors introduce a nonparametric method for testing for changes in the marginal distribution via empirical distribution functions (Csörg˝o and Horváth 1987; Carlstein 1988).”
Optimal rate of convergence for nonparametric change-point estimators for nonstationary sequences (2007, background): “1802 considered by Carlstein [4], who proposed an estimator, proved its consistency and determined a rate of convergence.”
Goodness-of-Fit Tests for Copulas of Multivariate Time Series (2017, unknown): “As remarked in Ghoudi and Rémillard (2010), that process appears as the limit of many other processes used in tests of change-point (Picard, 1985, Carlstein, 1988) and tests of independence (Blum et al., 1961, Ghoudi et al., 2001). Furthermore, tables for the limiting distribution of T (KS) j,n and ”
Inference for single and multiple change‐points in time series (2013, methodology): “This is important because it is easier to compute the estimator of Darkhovskh (1976) rather than that of Carlstein (1988).”