نتایج جستجو برای: residual test approximate maximum likelihood rt aml

تعداد نتایج: 1335768  

2006
Hossein Asgarian Mahdi Shabani Parvaneh Vosoogh Ramazan Ali Sharifian Soheila Gharagozlou Jalal Khoshnoodi Tahereh Shahrestani Mahin Kordmahin Abdolfattah Sarrafnejad Mahmood Jeddi Tehrani Hodjatallah Rabbani Fazel Shokri

Background: The Wilm’s tumor gene 1 (WT1) encodes a zinc finger transcription factor that is inactivated in a subset of Wilm’s tumors. It plays a crucial role in growth, proliferation and development of some embryonic and adult organs. WT1 is expressed as a tumor associated antigen (TAA) in various types of solid and hematopoietic malignancies and can be employed as a useful marker for targeted...

Journal: :Journal of bioinformatics and computational biology 2003
Louigi Addario-Berry Benny Chor Michael T. Hallett Jens Lagergren Alessandro Panconesi Todd Wareham

Maximum likelihood (ML) (Neyman, 1971) is an increasingly popular optimality criterion for selecting evolutionary trees. Finding optimal ML trees appears to be a very hard computational task--in particular, algorithms and heuristics for ML take longer to run than algorithms and heuristics for maximum parsimony (MP). However, while MP has been known to be NP-complete for over 20 years, no such h...

Journal: :Stochastic Processes and their Applications 1994

Journal: :Statistics and Computing 2020

1998
Dean Karlen

A method to approximate continuous multi-dimensional probability density functions (PDFs) using their projections and correlations is described. The method is particularly useful for event classification when estimates of systematic uncertainties are required and for the application of an unbinned maximum likelihood analysis when an analytic model is not available. A simple goodness of fit test...

Journal: :Applied sciences 2021

A local search Maximum Likelihood (ML) parameter estimator for mono-component chirp signal in low Signal-to-Noise Ratio (SNR) conditions is proposed this paper. The approach combines a deep learning denoising method with two-step estimator. denoiser utilizes residual assisted Denoising Convolutional Neural Network (DnCNN) to recover the structured component, which used denoise original observat...

Journal: :Applied Mathematics and Computation 2009
Chi-Chang Wang David T. W. Lin Hai-Ping Hu

This paper deals with application of the maximum principle for differential equations to the finite difference method for determining upper and lower approximate solutions of the non-linear Burgers’ equation and their error range. In term of mathematical architecture, the paper is based on the maximum principle for parabolic differential equations to establish monotonic residual relations of th...

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