Let $f_{n}(x)$ be the recursive kernel estimators of an unknown density function $f(x)$ at a given point $x$ . Also, let $N(t)(t>0)$ be a family of positive integer-valued random variables. We consider the sequential estimators $f_{N(t)}(x)$ . In this paper, under certain regularity conditions on $N(t)$ we shall show that $(N(t)h_{N(t)}^{p})^{1/2}(f_{N(i)}(x)-f(x))$ is asymptotically normally distributed as $t$ tends to infinity. Our conditions on $N(t)$ generalize those given by Carroll [2], Stute [9] and Isogai [6]
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Let $ f_n(x) $ be a recursive kernel estimator of a probability density function $ f $ at a point $ ...
The density estimator $f_{¥tau_{n}}(t)=T_{¥overline{n}^{1}}¥sum_{j=1}^{¥tau_{n}}h_{j}^{-1}K((t-X_{j}...
We consider an estimate of the mode θ of a multivariate probability density f with support in $\math...
The best mean square error that the classical kernel density estimator achieves if the kernel is non...
The best mean square error that the classical kernel density estimator achieves if the kernel is non...
The best mean square error that the classical kernel density estimator achieves if the kernel is non...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Let $ f_n(x) $ be a recursive kernel estimator of a probability density function $ f $ at a point $ ...
The density estimator $f_{¥tau_{n}}(t)=T_{¥overline{n}^{1}}¥sum_{j=1}^{¥tau_{n}}h_{j}^{-1}K((t-X_{j}...
We consider an estimate of the mode θ of a multivariate probability density f with support in $\math...
The best mean square error that the classical kernel density estimator achieves if the kernel is non...
The best mean square error that the classical kernel density estimator achieves if the kernel is non...
The best mean square error that the classical kernel density estimator achieves if the kernel is non...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let X1,…,Xn be i.i.d. observations, where Xi=Yi+snZi and the Y’s and Z’s are independent. Assume tha...
Let ZN, N≥1 denote the integer lattice points in the N-dimensional Euclidean space and be an Rd-valu...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...
Kernel type density estimators are studied for random fields. It is proved that the estimators are a...