Prediction of Loss Ratio Using Nonparametric Regression
نویسندگان
چکیده
منابع مشابه
Multi-period monitoring and prediction of forest cover loss using logistic regression model in Arasbaran catchments
Knowledge and understanding of changes in forest cover in relation to environmental factors (topography) can be valuable in terms of conservational and protective guidances. The purpose of this study was to identify, quantify and predict deforestation in relation to topographic variables using logistic regression model. The Arasbaran catchments (Naposhtehchay, Ilginehchay and Mardanqumchay) in ...
متن کاملOnline Nonparametric Regression with General Loss Functions
This paper establishes minimax rates for online regression with arbitrary classes of functions and general losses.1 We show that below a certain threshold for the complexity of the function class, the minimax rates depend on both the curvature of the loss function and the sequential complexities of the class. Above this threshold, the curvature of the loss does not affect the rates. Furthermore...
متن کاملMultivariate nonparametric regression using lifting
For regularly spaced one-dimensional data wavelet shrinkage has proven to be a compelling method for nonparametric function estimation. We argue that this is not the case for irregularly spaced data in two or higher dimensions. This article develops three methods for the multiscale analysis of irregularly spaced data based on the recently developed lifting paradigm by “lifting one coefficient a...
متن کاملLikelihood ratio confidence bands in nonparametric regression with censored data
Let (X,Y ) be a random vector, where Y denotes the variable of interest possibly subject to random right censoring, and X is a covariate. We construct confidence intervals and bands for the conditional survival and quantile function of Y given X using a nonparametric likelihood ratio approach. This approach was introduced by Thomas and Grunkemeier (1975), who estimated confidence intervals of s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: المجلة العلمیة للدراسات والبحوث المالیة والتجاریة
سال: 2021
ISSN: 2682-4531
DOI: 10.21608/cfdj.2020.129342