Search Results - empirical algorithmics

Handbook of high-frequency trading and modeling in finance

Table of Contents: “…5.3 Results obtained applying the model to real data5.3.1 part i: financial applications; 5.3.2 part ii: physical data application. temperature data; 5.3.3 part iii: analysis of seismometer readings during an earthquake; 5.3.4 analysis of the earthquake signal: beginning; 5.3.5 analysis: during the earthquake; 5.3.6 analysis: end of the earthquake signal, aftershocks; 5.4 Conclusion; Appendix 5.A:Theoretical results and empirical testing; 5.A.1 how does the particle filter work?…”
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Probability, Finance and Insurance : Proceedings of a Workshop. by Lai, T. L.

Table of Contents: “…Large and moderate deviations for self-normalized empirical processes; 7. Cramer type large deviations for independent random variables; 8. …”
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Dynamic factor models

Table of Contents: “…The FECM Form for Structural Analysis; 3. Data and empirical applications; 4. Forecasting macroeconomic variables; 4.1. …”
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Neural control engineering : the emerging intersection between control theory and neuroscience by Schiff, Steven J.

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Two-degree-of-freedom control systems : the Youla Parameterization approach by Keviczky, László, Bányász, Csilla

Table of Contents: “…POLE PLACEMENT WITH FEEDBACK REGULATORPOLE PLACEMENT WITH CHARACTERISTIC POLYNOMIAL DESIGN; 3.1 CONTROL LOOPS WITH STATE FEEDBACK; 3.2 STATE FEEDBACK LINEAR QUADRATIC (LQ) REGULATORS; 3.3 GENERAL POLYNOMIAL METHOD FOR REGULATOR DESIGN; Chapter 4 -- Concept of the Best Achievable Control; DECOMPOSITION OF SENSITIVITY FUNCTION; DECOMPOSITION OF SENSITIVITY FUNCTION FOR YP REGULATORS; DIRECT OPTIMIZATION OF SENSITIVITY FUNCTION; SPECIAL METHODS; EMPIRICAL RELATIONSHIPS; 4.1 OPTIMIZATION OF DESIGN LOSS; 4.2 OPTIMIZATION OF REALIZABILITY LOSS; 4.3 OPTIMIZATION OF MODELING LOSS.…”
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Performance evaluation and Army recruiting by Dertouzos, James N., 1950-

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Mathematics of evolution and phylogeny

Table of Contents: “…-- 9.6 Rearrangement algorithms -- 9.7 Loss of signal -- 9.8 From gene order to genomic sequence.; 9.8.1 The Pevzner-Tesler approach -- 9.8.2 The re-use statistic r -- 9.8.3 Simulating rearrangement inference with a block-size threshold -- 9.8.4 A model for breakpoint re-use -- 9.8.5 A measure of noise? …”
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Robust Battery Management Systems. by Balasingam, Balakumar

Table of Contents: “…-- 1.4.1 Modularized Approach -- 1.4.2 Illustration of Algorithms Through Matlab Simulation…”
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Inside the black box : a simple guide to quantitative and high frequency trading by Narang, Rishi K, 1974-

Table of Contents: “…Strategies Utilizing Price-Related DataStrategies Utilizing Fundamental Data; Data-Driven Alph a Models; Implementing the Strategies; Forecast Target; Time Horizon; Bet Structure; Investment Universe; Model Definition; Conditioning Variables; Run Frequency; An Explosion of Diversity; Blending Alpha Models; Summary; Notes; Chapter 4 Risk Models; Limiting the Amount of Risk; Limiting by Constraint or Penalty; Measuring the Amount of Risk; Where Limits Can Be Applied; Limiting the Types of Risk; Theory-Driven Risk Models; Empirical Risk Models; How Quants Choose a Risk Model; Summary; Notes.…”
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Evidencing the Productive Value of the 4IR in the AEC Sector. by Ejohwomu, Obuks A.

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Data Analysis and Applications 1 : New and Classical Approaches. by Skiadas, Christos

Table of Contents: “…From statistical learning theory to empirical validation…”
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The medical imagination : literature and health in the early United States by Altschuler, Sari

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Romance syntax, semantics and L2 acquisition : selected papers from the 30th Linguistic Symposium on Romance Languages : Gainesville, Florida, February 2000

Table of Contents: “…Discussion -- 6.1 The learning algorithm -- 6.2 Conceptualizing Learning.…”
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Computational materials engineering : achieving high accuracy and efficiency in metals processing simulations by Pietrzyk, Maciej, 1947-, Madej, Łukasz, Rauch, Lukasz, Szeliga, Danuta

Table of Contents: “…Toward Increase of the Efficiency of Modeling -- 2.1 Improvement of Numerical Algorithms -- 2.1.1 Metamodeling -- 2.1.2 Inverse analysis -- 2.1.2.1 General formulation of the inverse problem -- 2.1.2.2 Regularization -- 2.1.2.3 Methods of regularizations -- 2.1.2.4 Numerical computations and regularization in the finite-dimension setting -- 2.1.3 Sensitivity analysis -- 2.1.3.1 Local SA -- 2.1.3.2 Global SA -- 2.1.3.3 The implementation of SA algorithms -- 2.1.3.4 A strategy for the identification of the model parameters -- 2.2 Improvement of Hardware -- 2.2.1 General idea of high-performance computing -- 2.2.2 Development of clusters -- 2.2.3 Development of heterogeneous architectures -- 2.2.4 Development of grid environments -- 3. …”
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Reliability in biomechanics by Kharmanda, Ghias, El Hami, Abdelkhalak

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Discrete choice experiments in marketing : use of priors in efficient choice designs and their application to individual preference measurement by Zwerina, Klaus, 1967-

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Essentials of Monte Carlo Simulation : Statistical Methods for Building Simulation Models. by Thomopoulos, Nick T.

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Qualitative Spatial and Temporal Reasoning. by Ligozat, Gérard

Table of Contents: “…Ladkin and Reinefeld's algorithm; 2.4.2. Empirical study of the consistency problem; 2.5. …”
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Artificial intelligence research and development : current challenges, new trends and applications

Table of Contents: “…-- An Argumentation Approach for Agreement Analysis in Reddit Debates -- Tweet Sentiment Visualization and Classification Using Manifold Dimensionality Reduction -- N-Channel Convolutional Neural Networks for Irony Detection in Twitter -- A New Algorithm for Speech Enhancement Based on Multivariate Empirical Mode Decomposition -- Classifying and Generalizing Successful Parameter Combinations for Sound Design -- A Visual Distance for WordNet -- Enhancing Text Spotting with a Language Model and Visual Context Information -- Cognitive Systems and Agents -- What Is the Physics of Intelligence? …”
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Predictive Modeling of Pharmaceutical Unit Operations. by Pandey, Preetanshu

Table of Contents: “…Front Cover; Predictive Modeling of Pharmaceutical Unit Operations; Copyright Page; Contents; List of contributors; Predictive modeling of pharmaceutical unit operations; Preface; 1 Modeling of drug product manufacturing processes in the pharmaceutical industry; 1.1 Introduction; 1.2 Modeling techniques; 1.2.1 First principle predictive models; 1.2.1.1 Discrete element method; 1.2.1.2 Computational fluid dynamics; 1.2.1.3 Finite element method; 1.2.1.4 Hybrid models; 1.2.1.5 Empirical models; 1.3 Process modeling in drug product manufacturing; 1.3.1 Problem statement.…”
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