This paper introduces a new empirical strategy for the characterization of business cycles. It combines non-parametric decoding methods that classify a series into expansions and recessions but does not require specication of the underlying stochastic process generating the data. It then uses network analysis to combine the signals obtained from di erent economic indicators to generate a uniqu...

Multivariate control chats are generally used in situations where the simultaneous monitoring or control of two or more related quality characteristics is necessary. In most processes in the real world, distribution of the process characteristics are unknown or at least non-normal, so the non-parametric or distribution-free charts are desirable. Most non-parametric statistical process-control t...

We establish optimal rates for online regression for arbitrary classes of regression functions in terms of thesequential entropy introduced in [14]. The optimal rates are shown to exhibit a phase transition analogous to thei.i.d./statistical learning case, studied in [16]. In the frequently encountered situation when sequential entropyand i.i.d. empirical entropy match, our resu...

Background and Aim: Mucoepidermoid carcinoma (MEC) is the most common malignant neoplasm of the salivary glands with complex histopathologic features and clinical behavior. The aim of this study was to evaluate the clinicopathologic significance of p63, Maspin and matrix metalloproteinase (MMP)-2 expression in MEC. Materials and Methods: In this retrospective study, immunohistochemical stain...

ConvNets have been effective in many applications where it is required to learn invariances to within-class nuisance transformations. However, through their architecture, ConvNets only enforce invariance to translation. In this paper, we introduce a new class of convolutional architectures called Non-Parametric Transformation Networks (NPTNs) which can learn general invariances and symmetries d...

In most statistical problems treated in the literature a datum of the problem is the information that the various distributions of the chance variables involved belong to given families of distribution functions (d.f.'s) completely specified except for one or more parameters. Non-parametric statistical inference is concerned with problems where the d.f.'s are not specified to such an extent, an...

1 VaR (Value at Risk) estimates are currently based on two main techniques, the variance-covariance approach or simulation. Statistical and computational problems affect the reliability of these techniques. We illustrate a new technique, filtered historical simulation, that is designed to remedy some of the shortcomings of the simulation approach. We compare the estimates it produces with tradi...

The aim of this study was to evaluate the transitory stress levels and the anxiety state in children submitted to conventional and computerized dental anesthesia. Twenty children (7 to 12 years) were randomly assigned to receive conventional and computerized dental anesthesia. To investigate the hypothesis that transitory stress could be lower after using computerized anesthesia compared to con...

The views expressed in this paper are those of the author and do not necessarily reflect the views of the Arab Monetary Fund. Abstract While it is well documented that privatization leads to an improvement in the performance of state-owned enterprises (SOEs) following divestiture, it is argued that many of these studies do not consider the performance of control firms of similar pre-privatizati...

BACKGROUND The costing method used can change the results of economic evaluations. Choosing the appropriate method to assess the cost of organ recovery is an issue of considerable interest to health economists, hospitals, financial managers and policy makers in most developed countries. OBJECTIVES The main objective of this study was to compare a mixed method, combining top-down microcosting ...