Mooncakes and Milk Bread
Mooncakes and Milk Bread

Author: Kristina Cho

Publisher: Harper Celebrate

Published: 2021-10-12

Total Pages: 305

ISBN-13: 0785239006

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2022 JAMES BEARD AWARD WINNER • Baking and Desserts 2022 JAMES BEARD AWARD WINNER • Emerging Voice, Books ONE OF THE TEN BEST COOKBOOKS OF THE YEAR: The New Yorker Magazine, The New York Times ONE OF THE BEST COOKBOOKS OF THE YEAR: Time Out, Glamour, Taste of Home Food blogger Kristina Cho (eatchofood.com) introduces you to Chinese bakery cooking with fresh, simple interpretations of classic recipes for the modern baker. Inside, you’ll find sweet and savory baked buns, steamed buns, Chinese breads, unique cookies, whimsical cakes, juicy dumplings, Chinese breakfast dishes, and drinks. Recipes for steamed BBQ pork buns, pineapple buns with a thick slice of butter, silky smooth milk tea, and chocolate Swiss rolls all make an appearance--because a book about Chinese bakeries wouldn’t be complete without them In Mooncakes & Milk Bread, Kristina teaches you to whip up these delicacies like a pro, including how to: Knead dough without a stand mixer Avoid collapsed steamed buns Infuse creams and custards with aromatic tea flavors Mix the most workable dumpling dough Pleat dumplings like an Asian grandma This is the first book to exclusively focus on Chinese bakeries and cafés, but it isn’t just for those nostalgic for Chinese bakeshop foods--it’s for all home bakers who want exciting new recipes to add to their repertoires.

Discrete Choice Methods with Simulation
Discrete Choice Methods with Simulation

Author: Kenneth Train

Publisher: Cambridge University Press

Published: 2009-07-06

Total Pages: 399

ISBN-13: 0521766559

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This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.