Pages: 345, 6x9, English

Available Types: Print, E-book

Genre: Academic

Print book:

E-book: Rs.365 (PDF, delivered in 24 Working Hours)

There are many books on genetic statistics and quantitative genetics. These books expect different level of preparedness and analytical interventions emphasis on the formulation of real breeding data sets. This book is not introductory, it presumes various statistical and mathematical models demonstrated and derived considering by real breeding data sets. Reader are expected to know the essential of recent statistical tools such as sensor fusion estimation techniques, Kernel regression model, mathematical modeling on hardy Weinberg equilibrium, Pham kinetic genetic model, MLE's, OLR, weighted ordinary least square analysis, genetic correlation, heritability tested by advanced statistical tools, extraction of dummy variables from genetic and non-genetic components, random mating probability models, Risk analysis of human hereditary data by Bayesian approach, algorithms of sex linked inherited X-chromosomes, evaluation of pedigree through statistical approach, sex-linked recessive disorder of human population, data reduction techniques by snap shot techniques, Kal man filter estimation of multiple genetic traits, estimation of genetic variance, structural changes of genetic parameters, oscillation of genotypic and environmental variance, linear and nonlinear models etc. The main emphasis of the entire book is derivation of mathematical and statistical models to prove hardy Weinberg equilibrium at large random mating population. The present text book describes salient objectives and practical applicability to learn what methods are available and more importantly, when they should be applied in real life .Many examples are presented to clarify the use of the recent statistical techniques and to demonstrate what conclusions can be made at the right time modeling on genetics. Nevertheless, Statistical & mathematical modeling is a diversified area including many different topics illustrated by real breeding data sets. Furthermore, an advanced statistical technique has covered in the present edition. As per the genetic model formulation, a new technology is described in all the chapters. The PG students and research Scholars will easily extend the methods to enable for the compilation of high dimensional breeding datasets (Big data) generated from different experimental designs. Although the book narrowly focuses on a few topics, each topic Genetic fundamentals is provided with the partial derivatives. In collective terms, the statistical genetics is a multidisciplinary area with rapid developments, the present text book will helps to breeder's, researcher's and students to solve the real world problems of Genetics. For example, during the time between the completion of the first draft and the publication of this book, new methodologies and model formulation may have already been developed. Therefore, the book can only focus on the principles of advance statistical genetics. The present academic book intends to be used as a textbook for post graduate students in human, plant and animal genetics, but it can also be used by researchers as a reference book. For advanced readers, they can choose to read any particular chapters as they desire.