Two measures of sample entropy

By N. Ebrahimi, K. Pflughoeft, E. Soofi. 1994

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Citations in the corpus

Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks (2014, neutral): “As covariance function for HSIC, we use the popular Gaussian kernel: κ` : (x, x ′) 7→ exp ( −(x− x ′)2 `2 ) , with bandwidths selected by the median heuristic (Schölkopf and Smola, 2002), i.e., we take ˆ̀(u) := median{‖ui − uj‖ : 1 ≤ i j ≤ N, ‖ui − uj‖ 6= 0}, and similarly for ˆ̀(v).”
Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks (2014, background): “, 2004) 3NN ITE: Shannon kNN k (Kozachenko and Leonenko, 1987) sp1 ITE: Shannon spacing V (Vasicek, 1976) sp2 ITE: Shannon spacing Vb (Van Es, 1992) sp3 ITE: Shannon spacing Vpconst (Ebrahimi et al., 1994) sp4 ITE: Shannon spacing Vplin (Ebrahimi et al.”
Extropy estimators with applications in testing uniformity (2018, methodology): “By analogy to Ebrahimi, Pflughoeft, and Soofi (1994), we modify ai(m, n) as bi(m, n) = cim/nX(i+m) − X(i−m) , (4) where ci = ⎧⎪⎪⎪⎪⎨ ⎪⎪⎪⎪⎩ 1 + i − 1 m , 1 ≤ i ≤ m, 2, m + 1 i n − m, 1 + n − i m , n − m + 1 ≤ i ≤ n. (5) Therefore, the first extropy estimator JQ1mn was modified to JQ2mn given…”
Correcting moments for goodness of fit tests based on two entropy estimates (2003, methodology): “However, it has been noted in Ebrahimi et al. (1994) that the * Corresponding author.”
A NEW ESTIMATOR OF ENTROPY (2010, methodology): “Ebrahimi et al. (1994) and Alizadeh Noughabi (2010) have proposed estimates for the entropy of absolutely continuous random variables.”
On the entropy estimators (2013, methodology): “19 (1992), pp. 61–72], Ebrahimi et al. estimator and Correa estimator [A new estimator of entropy, Comm. Statist.”