表示向前
发表于 2025-4-1 05:53:37
Discretized Wavelet Density Estimators for Continuous Time Stochastic Processes,ch are satisfied for rather general diffusion processes, the. . error of the linear wavelet estimator of. constructed from the observation . converges with the rate . when . In this work we study two discretized versions of this estimator, constructed from the dicrete observations . We show that the
离开
发表于 2025-4-1 07:24:47
http://reply.papertrans.cn/103/10213/1021282/1021282_62.png
amplitude
发表于 2025-4-1 10:47:15
http://reply.papertrans.cn/103/10213/1021282/1021282_63.png
爵士乐
发表于 2025-4-1 16:51:50
http://reply.papertrans.cn/103/10213/1021282/1021282_64.png
Acupressure
发表于 2025-4-1 20:57:01
http://reply.papertrans.cn/103/10213/1021282/1021282_65.png
maudtin
发表于 2025-4-2 02:42:19
Choice of the Threshold Parameter in Wavelet Function Estimation, data. The choice of threshold is crucial to the success of the method and is currently subject to an intense research effort. We describe how we have applied the statistical technique of cross-validation to choose a threshold and we present results that indicate that its performance for correlated
恶意
发表于 2025-4-2 03:29:02
Choice of the Threshold Parameter in Wavelet Function Estimation, data. The choice of threshold is crucial to the success of the method and is currently subject to an intense research effort. We describe how we have applied the statistical technique of cross-validation to choose a threshold and we present results that indicate that its performance for correlated
夜晚
发表于 2025-4-2 08:23:43
The Stationary Wavelet Transform and some Statistical Applications,useful subsequently in the paper. A ‘stationary wavelet transform’, where the coefficient sequences are not decimated at each stage, is described. Two different approaches to the construction of an inverse of the stationary wavelet transform are set out. The application of the stationary wavelet tra
OWL
发表于 2025-4-2 11:57:17
http://reply.papertrans.cn/103/10213/1021282/1021282_69.png
STELL
发表于 2025-4-2 18:05:01
Wavelet Thresholding: Beyond the Gaussian I.I.D. Situation, of these applications are based on. of the empirical coefficients. For regression and density estimation with independent observations, we establish joint asymptotic normality of the empirical coefficients by means of strong approximations. Then we describe how one can prove asymptotic normality un