scholarly journals Threshold selection and trimming in extremes

Extremes ◽  
2020 ◽  
Vol 23 (4) ◽  
pp. 629-665
Author(s):  
Martin Bladt ◽  
Hansjörg Albrecher ◽  
Jan Beirlant
Keyword(s):  
Selection Procedure ◽  
Threshold Value ◽  
Extreme Value Statistics ◽  
Hill Estimator ◽  
Threshold Selection ◽  
Simple Ratio ◽  
Alternative Estimator ◽  
Insurance Data ◽  
Hill Plots ◽  
Selection Of

Abstract We consider removing lower order statistics from the classical Hill estimator in extreme value statistics, and compensating for it by rescaling the remaining terms. Trajectories of these trimmed statistics as a function of the extent of trimming turn out to be quite flat near the optimal threshold value. For the regularly varying case, the classical threshold selection problem in tail estimation is then revisited, both visually via trimmed Hill plots and, for the Hall class, also mathematically via minimizing the expected empirical variance. This leads to a simple threshold selection procedure for the classical Hill estimator which circumvents the estimation of some of the tail characteristics, a problem which is usually the bottleneck in threshold selection. As a by-product, we derive an alternative estimator of the tail index, which assigns more weight to large observations, and works particularly well for relatively lighter tails. A simple ratio statistic routine is suggested to evaluate the goodness of the implied selection of the threshold. We illustrate the favourable performance and the potential of the proposed method with simulation studies and real insurance data.

Identifying Measurement Invariant Item Sets in Cross-Cultural Settings Using an Automated Item Selection Procedure

Methodology ◽  
2018 ◽  
Vol 14 (4) ◽  
pp. 177-188 ◽  
Author(s):  
Martin Schultze ◽  
Michael Eid
Keyword(s):  
Measurement Invariance ◽  
Optimal Solution ◽  
Selection Procedure ◽  
Cross Cultural ◽  
Item Selection ◽  
Ant System ◽  
Item Quality ◽  
Ant System Algorithm ◽  
Selection For ◽  
Selection Of

Abstract. In the construction of scales intended for the use in cross-cultural studies, the selection of items needs to be guided not only by traditional criteria of item quality, but has to take information about the measurement invariance of the scale into account. We present an approach to automated item selection which depicts the process as a combinatorial optimization problem and aims at finding a scale which fulfils predefined target criteria – such as measurement invariance across cultures. The search for an optimal solution is performed using an adaptation of the [Formula: see text] Ant System algorithm. The approach is illustrated using an application to item selection for a personality scale assuming measurement invariance across multiple countries.

Combination of ribosome and phage display for fast selection of high affinity VHH antibody fragments

2019 ◽  
pp. 27-33
Author(s):  
YuE Kravchenko ◽  
SV Ivanov ◽  
DS Kravchenko ◽  
EI Frolova ◽  
SP Chumakov
Keyword(s):  
Phage Display ◽  
Selection Procedure ◽  
Free System ◽  
Phage Displays ◽  
High Affinity ◽  
Binding Domains ◽  
A Cell ◽  
Vhh Antibodies ◽  
Efficiency Of Selection ◽  
Selection Of

Selection of antibodies using phage display involves the preliminary cloning of the repertoire of sequences encoding antigen-binding domains into phagemid, which is considered the bottleneck of the method, limiting the resulting diversity of libraries and leading to the loss of poorly represented variants before the start of the selection procedure. Selection in cell-free conditions using a ribosomal display is devoid from this drawback, however is highly sensitive to PCR artifacts and the RNase contamination. The aim of the study was to test the efficiency of a combination of both methods, including pre-selection in a cell-free system to enrich the source library, followed by cloning and final selection using phage display. This approach may eliminate the shortcomings of each method and increase the efficiency of selection. For selection, alpaca VHH antibody sequences suitable for building an immune library were used due to the lack of VL domains. Analysis of immune libraries from the genes of the VH3, VHH3 and VH4 families showed that the VHH antibodies share in the VH3 and VH4 gene groups is insignificant, and selection from the combined library is less effective than from the VHH3 family of sequences. We found that the combination of ribosomal and phage displays leads to a higher enrichment of high-affinity fragments and avoids the loss of the original diversity during cloning. The combined method allowed us to obtain a greater number of different high-affinity sequences, and all the tested VHH fragments were able to specifically recognize the target, including the total protein extracts of cell cultures.

scholarly journals Threshold selection in univariate extreme value analysis

Extremes ◽  
2021 ◽  
Author(s):  
Laura Fee Schneider ◽  
Andrea Krajina ◽  
Tatyana Krivobokova
Keyword(s):  
Mean Squared Error ◽  
Extreme Value ◽  
Hill Estimator ◽  
Small Samples ◽  
Extreme Value Analysis ◽  
Threshold Selection ◽  
Value Analysis ◽  
Wide Range ◽  
Asymptotic Mean Squared Error ◽  
The Hill

AbstractThreshold selection plays a key role in various aspects of statistical inference of rare events. In this work, two new threshold selection methods are introduced. The first approach measures the fit of the exponential approximation above a threshold and achieves good performance in small samples. The second method smoothly estimates the asymptotic mean squared error of the Hill estimator and performs consistently well over a wide range of processes. Both methods are analyzed theoretically, compared to existing procedures in an extensive simulation study and applied to a dataset of financial losses, where the underlying extreme value index is assumed to vary over time.

scholarly journals Monotonic Functions Method and Its Application to Staging of Patients with Prostate Cancer According to Pretreatment Data

2021 ◽  
Vol 11 (9) ◽  
pp. 3836
Author(s):  
Valeri Gitis ◽  
Alexander Derendyaev ◽  
Konstantin Petrov ◽  
Eugene Yurkov ◽  
Sergey Pirogov ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Learning Algorithm ◽  
Binary Classification ◽  
Preoperative Staging ◽  
Threshold Value ◽  
Logical Function ◽  
Adequate Treatment ◽  
Monotonic Functions ◽  
Selection Of

Prostate cancer is the second most frequent malignancy (after lung cancer). Preoperative staging of PCa is the basis for the selection of adequate treatment tactics. In particular, an urgent problem is the classification of indolent and aggressive forms of PCa in patients with the initial stages of the tumor process. To solve this problem, we propose to use a new binary classification machine-learning method. The proposed method of monotonic functions uses a model in which the disease’s form is determined by the severity of the patient’s condition. It is assumed that the patient’s condition is the easier, the less the deviation of the indicators from the normal values inherent in healthy people. This assumption means that the severity (form) of the disease can be represented by monotonic functions from the values of the deviation of the patient’s indicators beyond the normal range. The method is used to solve the problem of classifying patients with indolent and aggressive forms of prostate cancer according to pretreatment data. The learning algorithm is nonparametric. At the same time, it allows an explanation of the classification results in the form of a logical function. To do this, you should indicate to the algorithm either the threshold value of the probability of successful classification of patients with an indolent form of PCa, or the threshold value of the probability of misclassification of patients with an aggressive form of PCa disease. The examples of logical rules given in the article show that they are quite simple and can be easily interpreted in terms of preoperative indicators of the form of the disease.

scholarly journals Gradient boosting for linear mixed models

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Colin Griesbach ◽  
Benjamin Säfken ◽  
Elisabeth Waldmann
Keyword(s):  
Random Effects ◽  
Mixed Models ◽  
Selection Procedure ◽  
Classification Theory ◽  
Gradient Boosting ◽  
Random Structure ◽  
Boosting Algorithm ◽  
The One ◽  
Biased Estimates ◽  
Selection Of

Abstract Gradient boosting from the field of statistical learning is widely known as a powerful framework for estimation and selection of predictor effects in various regression models by adapting concepts from classification theory. Current boosting approaches also offer methods accounting for random effects and thus enable prediction of mixed models for longitudinal and clustered data. However, these approaches include several flaws resulting in unbalanced effect selection with falsely induced shrinkage and a low convergence rate on the one hand and biased estimates of the random effects on the other hand. We therefore propose a new boosting algorithm which explicitly accounts for the random structure by excluding it from the selection procedure, properly correcting the random effects estimates and in addition providing likelihood-based estimation of the random effects variance structure. The new algorithm offers an organic and unbiased fitting approach, which is shown via simulations and data examples.

scholarly journals Sistem Pendukung Keputusan Pemilihan Mobil Bekas Menggunakan Metode Analythical Hierarchy Process

2021 ◽  
Vol 3 (2) ◽  
pp. 380-386
Author(s):  
Gushelmi Gushelmi ◽  
Dodi Guswandi
Keyword(s):  
Selection Process ◽  
Threshold Value ◽  
Internet Technology ◽  
A Value ◽  
Used Cars ◽  
Hierarchy Process ◽  
Selection Of ◽  
Comparison Data

Showroom Ragasa Motor Padang is a showroom that sells various types of used cars. The old system of selecting used cars in The Ragasa Motor Padang Showroom is that customers come directly to the address of this Showroom and the selection process is still done by manual means. With the development of internet technology today is increasing rapidly and in order to be accessible to everyone, the AHP can do a comparison of the criteria in pairs on the selection of used cars and can determine the consistency of the comparison data paired with a threshold value of < 0.1. The purpose of this research is to make it easier for customers to choose used cars quickly and accurately, as well as the application of programs used to make it easier for customers to use them. The result of this study is the SPK System that was built to be able to take the decision of the selection of used cars in the Showroom Ragasa Motor Padang with the selection of the 2nd alternative with a value of 2.55 as the best choice.

scholarly journals Selection of the most adequate trip-modelling tool for integrated transport planning system

2016 ◽  
Vol 37 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Piotr Sawicki ◽  
Marcin Kiciński ◽  
Szymon Fierek
Keyword(s):  
Selection Criteria ◽  
Selection Process ◽  
Regional Scale ◽  
Selection Procedure ◽  
Planning System ◽  
Second Phase ◽  
Transport Planning ◽  
Phase Selection ◽  
Technical Requirements ◽  
Selection Of

This paper deals with the problem of selection the most suitable trip-modelling tool (TMT), which is a part of the more complex integrated transport planning system (ITPS) at the regional scale. Since an application of TMT is not autonomous and several different users exist the selection problem is not a trivial. In this paper, an original five-phase selection procedure is presented. The first phase consists in specifica¬tion of both, detailed expectations of all identified users and technical requirements of ITPS. Second phase deals with research on available TMT while a third one is concentrated on defining a comprehensive set of criteria. In this phase critical criteria as well as selection criteria are defined. First one is utilised to eliminate unacceptable TMTs in phase four and second one to evaluate and select most adequate TMT in phase five. In the paper an exemplary application of this procedure is presented. The authors have defined 2 critical criteria and a set of 19 selection criteria. The last one is divided into 3 main subsets, i.e. functional, technical and financial contexts of selection process. All the selection criteria are characterised by 43 sub-criteria and some of them are more detailed extended. Using this procedure 3 out of 6 alternative TMTs including Emme, Aimsun and Visum have been initially accepted and next evaluated. Finally, Visum has been selected and recommended for application into ITPS.

scholarly journals Layer contour characterization in additive manufacturing through image binarization

2021 ◽  
Vol 1193 (1) ◽  
pp. 012067
Author(s):  
D Blanco ◽  
A Fernández ◽  
P Fernández ◽  
B J Álvarez ◽  
F Peña
Keyword(s):  
Digital Images ◽  
Median Filter ◽  
Threshold Value ◽  
Image Binarization ◽  
Actual Contour ◽  
Filter Size ◽  
Characterization Procedure ◽  
Flat Bed Scanner ◽  
Selection Of ◽  
Excellent Coverage

Abstract On-Machine Measurement adoption will be key to dimensional and geometrical improvement of additively manufactured parts. One possible approach based on OMM aims at using digital images of manufactured layers to characterize actual contour deviations with respect to their theoretical profile. This strategy would also allow for in-process corrective actions. This work describes a layer-contour characterization procedure based on binarization of digital images acquired with a flat-bed scanner. This procedure has been tested off-line to evaluate the influence of two of the parameters for image treatment, the median filter size (S f ) and the threshold value (T), on the dimensional/geometrical reliability of the contour characterization. Results showed that an appropriate selection of configuration parameters allowed to characterize the proposed test-target with excellent coverage and reasonable accuracy.

scholarly journals Mean-Based Breakpoint Selection on Circular Histogram

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jiulun Fan ◽  
Jipeng Yang
Keyword(s):  
Selection Criteria ◽  
Color Image ◽  
Selection Criterion ◽  
Threshold Value ◽  
Simple Expression ◽  
Circular Data ◽  
Cumulative Distribution ◽  
Color Model ◽  
Hsi Color Model ◽  
Selection Of

Circular histogram represents the statistical distribution of circular data; the H component histogram of HSI color model is a typical example of the circular histogram. When using H component to segment color image, a feasible way is to transform the circular histogram into a linear histogram, and then, the mature gray image thresholding methods are used on the linear histogram to select the threshold value. Thus, the reasonable selection of the breakpoint on circular histogram to linearize the circular histogram is the key. In this paper, based on the angles mean on circular histogram and the line mean on linear histogram, a simple breakpoint selection criterion is proposed, and the suitable range of this method is analyzed. Compared with the existing breakpoint selection criteria based on Lorenz curve and cumulative distribution entropy, the proposed method has the advantages of simple expression and less calculation and does not depend on the direction of rotation.

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