APPROXIMATION RATES OF ERROR DISTRIBUTION OF DOUBLE KERNEL ESTIMATES OF CONDITIONAL DENSITY

§ 1　IntroductionLet(X,Y) be a random vector taking values Rp×Rqand assume that with given X=x,f(y|x) is the conditional density of Y,the Borel-measurable function on(x,y) ,X has amarginal distribution function F(x) and a marginal density function f(x) .Let(X1 ,Y1 ) ,...,(Xn,Yn) be i.i.d.sample taking values in(X,Y) .A class of double kernel esti-mates of f(y|x) proposed by Zhao Linchang and Liu Zhijun[1 ] has the formfn(y|x) = ni=1K1Xi -xan K2Yi -ybn bqn nj=1K1Xj-xan ,(1 .1 )where…     

BMO ESTIMATES FOR MULTILINEAR FRACTIONAL INTEGRALS

In this paper,the authors prove that the multilinear fractional integral operator T A 1,A 2 ,α and the relevant maximal operator M A 1,A 2 ,α with rough kernel are both bounded from L p (1 p ∞) to L q and from L p to L n/(n α),∞ with power weight,respectively,where T A 1,A 2 ,α (f)(x)=R n R m 1 (A 1 ;x,y)R m 2 (A 2 ;x,y) | x y | n α +m 1 +m 2 2 (x y) f (y)dy and M A 1,A 2 ,α (f)(x)=sup r0 1 r n α +m 1 +m 2 2 | x y | r 2 ∏ i=1 R m i (A i ;x,y)(x y) f (y) | dy,and 0 α n, ∈ L s (S n 1) (s ≥ 1) is a homogeneous function of degree zero in R n,A i is a function defined on R n and R m i (A i ;x,y) denotes the m i t h remainder of Taylor series of A i at x about y.More precisely,R m i (A i ;x,y)=A i (x) ∑ | γ | m i 1 γ ! D γ A i (y)(x y) r,where D γ (A i) ∈ BMO(R n) for | γ |=m i 1(m i 1),i=1,2.     

ASYMPTOTICS OF THE RESIDUALS DENSITY ESTIMATION IN NONPARAMETRIC REGRESSION UNDER m（n）-DEPENDENT SAMPLE

Let Y_i=M(X_i)+ei, where M(x)=E(Y|X=x) is an unknown realfunction on B(? R), {(X_1,Y_i)} is a stationary and m(n)-dependent sample from(X, Y), the residuals {e_i} are independent of {X_i} and have unknown common densityf(x). In [2] a nonparametric estimate f_n(x) for f(x) has been proposed on the basisof the residuals estimates. In this paper, we further obtain the asymptotic normalityand the law of the iterated logarithm of f_n(x) under some suitable conditions. Theseresults together with those in [2] bring the asymptotic theory for the residuals densityestimate in nonparametric regression under m(n)-dependent sample to completion.     

Strong Consistency of Non-parametric Regression Estimates with Censored Data

Let (X,Y) be an R~d×R valued random vector with E|Y|<∞ and(X_1,Y_1) (X_2,Y_2), …, (X_n,Y_n) be i.i.d.observations of (X,Y). To estimate the regression function m(x)=E(Y|X=x), Stone suggested m_n(x)=sum from i=1 to n(W_(ni)(x)Y_i), where W_(ni)(x)=W_(ni)(x,X_1,X_2,…,X_n)(i=1,2,…,n) are weight functions. Devroye and Chen Xiru established the strong consistency of m_n(x). In this paper, we discuss the case that{Y_i} are censored by {t_i}, where{t_i} are i.i.d. random variables and also independent of{Y_i}. Under certainconditions we still obtain the strong consistency of m_n(x).     

THE ALEKSANDROV PROBLEM FOR UNIT DISTANCE PRESERVING MAPPING

1 IntroductionLet X and Y be two real metric spaces. A mappillg f: X ~ Y is called an isometryj ifd(f(x), f(y)) = d(x, y) for all x, y E X.A mapping f: X - Y satisfies the distance one preserving property (DOPP) if f for allx, y E X with d(x, y) = 1 it follows that d(f(x), f(y)) = 1.A mapping f: X ~ Y satisfies the strong distance one preserving property (SDOPP) ifffor all x, y E X with d(x, y) = 1 it follows that d(f(x), f(y)) = 1 and conversely.Problem(P) Let f: X - Y be a mappin…     

条件密度双重核估计误差分布的逼近速度

In this paper, the normal approximation rate and the random weighting approximation rate of error distribution of the kernel estimator of conditional density function f(y!|x) are studied. The results may be used to construct the confidence interval of f(y|x).     

STRONG CONVERGENCE OF KERNEL ESTIMATES OF NONPARAMETRIC REGRESSION FUNCTIONS

Let (X, Y), (X_1, Y_1), …, (X_n, Y_n) be i. i. d. random vectors taking values in R_d×Rwith E(|Y|)<∞. To estimate the regression function m (x) = E (Y|X= x), we use thekernel estimate m_n(x)= sum from i=1 to n K((X_j-x)/h_n) where K(x) is a kernel functionand h_n a window width. In this paper, we establish the strong consistency of m_n(x) whenE(|Y|~P)<∞ for some p>l or E{exp(t|Y|~λ)}<∞ for some λ>0 and t>O. It is remakablethat other conditions imposed here are independent of the distribution of (X, Y).     

A relative local variational principle for topological pressure

We define the relative local topological pressure for any given factor map and open cover,and prove the relative local variational principle of this pressure.More precisely,for a given factor map π:(X,T)→(Y,S) between two topological dynamical systems,an open cover U of X,a continuous,real-valued function f on X and an S-invariant measure ν on Y,we show that the corresponding relative local pressure P(T,f,U,y) satisfies sup μ∈M(X,T){ hμ(T,U|Y)+∫X f(x)dμ(x) :πμ=ν}=∫Y P(T,f,U,y)dν(y),where M(X,T) denotes the family of all T-invariant measures on X.Moreover,the supremum can be attained by a T-invariant measure.     

More on stability of almost surjective ε-isometries of Banach spaces

Let X and Y be two Banach spaces,and f:X→Y be a standard ε-isometry for some ε = 0.In this paper,by using a recent theorem established by Cheng et al.(2013–2015),we show a sufficient condition guaranteeing the following sharp stability inequality of f:There is a surjective linear operator T:Y→X of norm one so that ||T f(x)-x||= 2ε,for all x∈X.As its application,we prove the following statements are equivalent for a standard ε-isometry f:X→Y:(i)lim inf_(t→∞) dist(ty,f(X))/|t|1/2,for all y∈S_Y;(ii)τ(f)≡sup_(y∈S_Y) lim inf_(t→∞) dist(ty,f(X))/|t|=0;(iii)there is a surjective linear isometry U:X→Y so that || f(x)-Ux||= 2ε,for all x∈X.This gives an affirmative answer to a question proposed by Vestfrid(2004,2015).     

Sufficient and Necessary Condition for the Measurability of Fallable Fuzzy Sets

Let(X,)be a measurable space,and,=σ-field generated by {x|x∈X},where x={A∈ |x∈A}.(Y,)another measurable space,let ρ(X, Y,)={∈ |§ be measurable}.∈ρ(X,Y,),we define ()(y)=~(-1)(y),y∈y. Defination 1.T is an index set,f:{0,1}~T→{0,1},then,O~T:( (Y)~x)~T→ (Y)~x is called the operation derived from f if for any { }_(t∈T)∈((Y)~x)~Tand any(x,y)∈X×Y,it holds     

Comparison of variance estimators for the ratio estimator based on small sample

1. Introduction and Main ResultsSuppose the population of interest consists of N distinct units labelled by 1,' f N.Associated with unit i are two values K and Xi, with Xi > 0 (i = 1,' t N). Denote thepopulation means of K and X, by Y and X respectively. To estimate Y, it is customaryto select a simple raPdom sample of size n and to use the ratio estimatNn = RX if Xis available, where R = y/x is an estimator for population ratio R = Y/X, y and x arerespectively the 8ample mean8 of…     

A LAW OF THE ITERATED LOGARITHM FOR NEAREST NEIGHBOR ESTIMATION OF MULTIVARIATE DENSITY FUNCTION

Let X be a d-dimensional random vector with unknown density function f(z)=f(z_1, ···, z_d), and let f_n be teh nearest neighbor estimator of f proposed by Loftsgaarden and Quesenberry (1965). In this paper, we established the law of the iterated logarithm of f_n for general case of d≥1, which gives the exact pointwise strong convergence rate of f_n.     

ON THE PROBLEM OF NECESSARY CONDITIONS ENSURING UNIFORM CONVERGENCE OF KERNEL DENSITY ESTIMATES

Let X_1,…,X,be a sequence of p-dimensional iid.random vectors with a commondistribution F(x).Denote the kernel estimate of the probability density of F(if it exists)by_n(x)=n~(-1)h~_n(-p)K((x-X_i)/h_n)Suppose that there exists a measurable function g(x)and h_n>0,h_n→0 such thatlim sup丨f_n(x)-g(x)丨=0 a.s.Does F(x)have a uniformly continuous density function f(x)and f(x)=g(x)?This paperdeals with the problem and gives a sufficient and necessary condition for generalp-dimensional case.     

ISOMETRIES OF THE UNITE SPHERE

It is extended that DARYL TINGLEY's results about that isometries between the unit sphereo of finite dimensional Banach Spaces necessarily map antipodal points to antipodal points.Now, the results is obtained in strictly convex (or l_1) spaces, i.e.: If X, Y are two strictly convex (or l_1) spaces, and S(X), S(Y) are the unit spheres of X and Y respectively,f: is an isometry, then f(-x)= - f(x), for any x in S(X).     

On the Pointwisise L_p Convergence Rates of Nearest Neighbor Estimate of Nonparametric Regression Function

Let (X,y) be a R~d×R~1-valued radom vector with E(?)=E(Y|X=x) be the regression funvion of Y with respect to X.Su (X_i, Y_i),i=1, …,n, are iid samples drawn ftc, from (X,Y).(?)desired to estimate m(x) based on these samples,everoye discussed in (?) the pointwise convergence of the nearest neigthoor estimate m_n(X) (see (5) of the present paper). Ih this article we further study the rate of this eonyer-gence.It is shown that if there exists p≥2 sach that E 、|Y|<∞,then for suitabte choice of the weighte C_m (see(4) of the present paper).     

Comonotone approximation with interpolation at the ends on an interval

Let a function f ∈ C[-1, 1], changes its monotonisity at the finite collection Y := {y1,… ,ys} of s points yi ∈ (-1, 1). For each n ≥ N(Y), we construct an algebraic polynomial Pn, of degree ≤ n, which is comonotone with f, that is changes its monotonisity at the same points yi as f, and |f(x)-Pn(x)|≤c(s)ω2(f,(√1-x2)/n), x∈[-1,1],where N(Y) is a constant depending only on Y, c(s) is a constant depending only on s and ω2 (f, t) is the second modulus of smoothness of f.     

负相依随机变量的自正则化中心极限定理与部分和的方差估计

§ 1　 IntroductionWe firstintroduce some concepts.Random variables X and Y are called negative dependent ( ND) if for any pair ofmonotonically non-decresing functions f and g,Cov{ f( X) ,g( Y) }≤ 0 .Clearly itis equivalenttoP( X≤ x,Y≤ y)≤ P( X≤ x) P( Y≤ y)for all x,y∈R.A random sequence{ Xi,i≥ 1 } is said to be negative quadrant dependent( NQD) if any pairof variables Xi,Xj( i≠j) are ND.A sequence of random variables{ Xi,i≥ 1 } is said to be linear negative quadrand depend…     

QUADRATIC ρ-FUNCTIONAL INEQUALITIES IN BANACH SPACES

In this paper,we solve the quadratic p-functional inequalities‖f(x+y)+f(x-y)-2f(x)-2f(y)‖≤‖ρ(2f((x+y)/2)+2f((x-y)/2)-f(x)-f(y))‖,(0.1)where ρ is a fixed complex number with |ρ| 1,and‖2f((x+y)/2)+2f((x-y)/2)-f(x)-f(y)‖≤‖ρ(f(x+y)+f(x-y)-2f(x)-2f(y))‖,(0.2)where ρ is a fixed complex number with |ρ| 1/2.Using the direct method,we prove the Hyers-Ulam stability of the quadratic ρ-functional inequalities(0.1) and(0.2) in complex Banach spaces and prove the Hyers-Ulam stability of quadratic ρ-functional equations associated with the quadratic ρ-functional inequalities(0.1)and(0.2) in complex Banach spaces.     

非参数回归函数的随机窗宽核估计的重对数律

设(X,Y),(X_1,Y_1),(X_2,Y_2),…为 i.i.d.二维随机变量序列,具有联合分布F(x,y)及密度 f(x,y).X 的边际分布和密度分别记为 F_X(x)和 f_X(x).记 m(x)=E{Y|X=x)}为 Y 对 X 的回归函数.为估计 m(x),Nadaraya 和 watson 独立地引进了如下形式的核估计     

HIGHER C0MMUTATORS OF PSEUDODIFFERENTIAL OPERATORS

In this paper the following result is established: For a_i, f∈(R~K), i=1, …, n, and T (a, f) (x)=ω(x, D)(multiply from i=1 to n P_(mi)(a_i, x, ·)f(·)),it holds that ‖T(a, f)‖_q≤C‖f‖_(po) multiply from i=1 to n ~m_ia_i‖_(p_4),where a=(a_1, …, a_n), q~(-1)=p_0~(-1)+ sum from i=1 to n p_i~(-1)∈(O, 1), p_i∈(1, ∞)or i, p_i=∞, p_0∈(1, ∞),for an integer m_i≥0, P_(m_1)(a_i, x, y)=a_i(x)-∑ |β|相似文献