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Investigating the Role of Test Methods in Testing Reading Comprehension - Jufang Kong - Bog - Springer Verlag, Singapore - Plusbog.dk

VLSI Design and Test - - Bog - Springer Verlag, Singapore - Plusbog.dk

VLSI Design and Test - - Bog - Springer Verlag, Singapore - Plusbog.dk

Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test - Xun Chen - Bog - Springer Verlag, Singapore - Plusbog.dk

Post-Brexit Europe and UK - - Bog - Springer Verlag, Singapore - Plusbog.dk

Test Configurations, Stabilities and Canonical Kahler Metrics - Toshiki Mabuchi - Bog - Springer Verlag, Singapore - Plusbog.dk

Principal Component Analysis and Randomness Test for Big Data Analysis - Mieko Tanaka Yamawaki - Bog - Springer Verlag, Singapore - Plusbog.dk

Principal Component Analysis and Randomness Test for Big Data Analysis - Mieko Tanaka Yamawaki - Bog - Springer Verlag, Singapore - Plusbog.dk

This book presents the novel approach of analyzing large-sized rectangular-shaped numerical data (so-called big data). The essence of this approach is to grasp the "meaning" of the data instantly, without getting into the details of individual data. Unlike conventional approaches of principal component analysis, randomness tests, and visualization methods, the authors' approach has the benefits of universality and simplicity of data analysis, regardless of data types, structures, or specific field of science. First, mathematical preparation is described. The RMT-PCA and the RMT-test utilize the cross-correlation matrix of time series, C = XXT, where X represents a rectangular matrix of N rows and L columns and XT represents the transverse matrix of X. Because C is symmetric, namely, C = CT, it can be converted to a diagonal matrix of eigenvalues by a similarity transformation SCS-1 = SCST using an orthogonal matrix S. When N is significantly large, the histogram of the eigenvalue distribution can be compared to the theoretical formula derived in the context of the random matrix theory (RMT, in abbreviation). Then the RMT-PCA applied to high-frequency stock prices in Japanese and American markets is dealt with. This approach proves its effectiveness in extracting "trendy" business sectors of the financial market over the prescribed time scale. In this case, X consists of N stock- prices of length L, and the correlation matrix C is an N by N square matrix, whose element at the i-th row and j-th column is the inner product of the price time series of the length L of the i-th stock and the j-th stock of the equal length L. Next, the RMT-test is applied to measure randomness of various random number generators, including algorithmically generated random numbers and physically generated random numbers. The book concludes by demonstrating two applications of the RMT-test: (1) a comparison of hash functions, and (2) stock prediction by means of randomness, including a new index of off-randomness related to market decline.

DKK 901.00
1

Numerical Modeling of Soil Constitutive Relationship - Jianting Zhou - Bog - Springer Verlag, Singapore - Plusbog.dk

Numerical Modeling of Soil Constitutive Relationship - Jianting Zhou - Bog - Springer Verlag, Singapore - Plusbog.dk

Asymptotic Statistical Inference - Shailaja Deshmukh - Bog - Springer Verlag, Singapore - Plusbog.dk

Asymptotic Statistical Inference - Shailaja Deshmukh - Bog - Springer Verlag, Singapore - Plusbog.dk

The book presents the fundamental concepts from asymptotic statistical inference theory, elaborating on some basic large sample optimality properties of estimators and some test procedures. The most desirable property of consistency of an estimator and its large sample distribution, with suitable normalization, are discussed, the focus being on the consistent and asymptotically normal (CAN) estimators. It is shown that for the probability models belonging to an exponential family and a Cramer family, the maximum likelihood estimators of the indexing parameters are CAN. The book describes some large sample test procedures, in particular, the most frequently used likelihood ratio test procedure. Various applications of the likelihood ratio test procedure are addressed, when the underlying probability model is a multinomial distribution. These include tests for the goodness of fit and tests for contingency tables. The book also discusses a score test and Wald''s test, their relationship with the likelihood ratio test and Karl Pearson''s chi-square test. An important finding is that, while testing any hypothesis about the parameters of a multinomial distribution, a score test statistic and Karl Pearson''s chi-square test statistic are identical. Numerous illustrative examples of differing difficulty level are incorporated to clarify the concepts. For better assimilation of the notions, various exercises are included in each chapter. Solutions to almost all the exercises are given in the last chapter, to motivate students towards solving these exercises and to enable digestion of the underlying concepts. The concepts from asymptotic inference are crucial in modern statistics, but are difficult to grasp in view of their abstract nature. To overcome this difficulty, keeping up with the recent trend of using R software for statistical computations, the book uses it extensively, for illustrating the concepts, verifying the properties of estimators and carrying out various test procedures. The last section of the chapters presents R codes to reveal and visually demonstrate the hidden aspects of different concepts and procedures. Augmenting the theory with R software is a novel and a unique feature of the book. The book is designed primarily to serve as a text book for a one semester introductory course in asymptotic statistical inference, in a post-graduate program, such as Statistics, Bio-statistics or Econometrics. It will also provide sufficient background information for studying inference in stochastic processes. The book will cater to the need of a concise but clear and student-friendly book introducing, conceptually and computationally, basics of asymptotic inference.

DKK 646.00
1

Diagnostic Methods in Time Series - Anna Clara Monti - Bog - Springer Verlag, Singapore - Plusbog.dk

Diagnostic Methods in Time Series - Anna Clara Monti - Bog - Springer Verlag, Singapore - Plusbog.dk

This book contains new aspects of model diagnostics in time series analysis, including variable selection problems and higher-order asymptotics of tests. This is the first book to cover systematic approaches and widely applicable results for nonstandard models including infinite variance processes. The book begins by introducing a unified view of a portmanteau-type test based on a likelihood ratio test, useful to test general parametric hypotheses inherent in statistical models. The conditions for the limit distribution of portmanteau-type tests to be asymptotically pivotal are given under general settings, and very clear implications for the relationships between the parameter of interest and the nuisance parameter are elucidated in terms of Fisher-information matrices. A robust testing procedure against heavy-tailed time series models is also constructed in the context of variable selection problems. The setting is very reasonable in the context of financial data analysis and econometrics, and the result is applicable to causality tests of heavy-tailed time series models. In the last two sections, Bartlett-type adjustments for a class of test statistics are discussed when the parameter of interest is on the boundary of the parameter space. A nonlinear adjustment procedure is proposed for a broad range of test statistics including the likelihood ratio, Wald and score statistics.

DKK 519.00
1

Multiple Comparisons for Bernoulli Data - Taka Aki Shiraishi - Bog - Springer Verlag, Singapore - Plusbog.dk

Geological Disaster Monitoring Based on Sensor Networks - - Bog - Springer Verlag, Singapore - Plusbog.dk

Recycled Polyester - - Bog - Springer Verlag, Singapore - Plusbog.dk

Determining Sample Size and Power in Research Studies - Priyam Verma - Bog - Springer Verlag, Singapore - Plusbog.dk

Determining Sample Size and Power in Research Studies - Priyam Verma - Bog - Springer Verlag, Singapore - Plusbog.dk

This book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.

DKK 986.00
1

Determining Sample Size and Power in Research Studies - J. P. Verma - Bog - Springer Verlag, Singapore - Plusbog.dk

Determining Sample Size and Power in Research Studies - J. P. Verma - Bog - Springer Verlag, Singapore - Plusbog.dk

This book addresses sample size and power in the context of research, offering valuable insights for graduate and doctoral students as well as researchers in any discipline where data is generated to investigate research questions. It explains how to enhance the authenticity of research by estimating the sample size and reporting the power of the tests used. Further, it discusses the issue of sample size determination in survey studies as well as in hypothesis testing experiments so that readers can grasp the concept of statistical errors, minimum detectable difference, effect size, one-tail and two-tail tests and the power of the test. The book also highlights the importance of fixing these boundary conditions in enhancing the authenticity of research findings and improving the chances of research papers being accepted by respected journals. Further, it explores the significance of sample size by showing the power achieved in selected doctoral studies. Procedure has been discussed to fix power in the hypothesis testing experiment. One should usually have power at least 0.8 in the study because having power less than this will have the issue of practical significance of findings. If the power in any study is less than 0.5 then it would be better to test the hypothesis by tossing a coin instead of organizing the experiment. It also discusses determining sample size and power using the freeware G*Power software, based on twenty-one examples using different analyses, like t-test, parametric and non-parametric correlations, multivariate regression, logistic regression, independent and repeated measures ANOVA, mixed design, MANOVA and chi-square.

DKK 800.00
1

Best Practice Protocols for Physique Assessment in Sport - - Bog - Springer Verlag, Singapore - Plusbog.dk