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161Table of Contents: “...There are hidden costs with improved safety -- Perhaps the insurance revolution starts with buses -- Mercedes-Benz and Germany: A case study in liability -- German law provides further clarification -- How liability is apportioned in Germany -- What the insurers say about liability for driverless cars -- Future predictions: Its time to standardize the standards -- Stars and crash dummies -- From an information program to a new standard -- Who sets the standards for ADAS tests and driverless technology -- How they do NCAP in Europe -- The inventors no longer like their invention -- Summary: Making policies for affordable mobility -- Chapter 10: Making it happen -- Introduction: Design and analysis of deployment scenarios -- Principles: Modeling the demand side -- Step 1: Creation of the Princeton Nationwide person file -- Step 2: Creation of the Princeton Nationwide PersonTrip file -- Journey to school -- Journey to work -- Journey to other places -- Current conditions: Modeling the supply side -- The scope of the supply side -- Walking -- Conventional bus transit trips -- Conventional rail transit trips -- Trips involving airlines that serve long trips -- Trips within the operational design domain (ODD) of the demand-responsive system -- The MOVES-style operational design concept -- MOVES-style design and data visualization -- MOVES mode split process -- MOVES operational simulation and animation -- MOVES basic economic analysis -- MOVES kiosk design concepts -- MOVES community involvement concepts -- Future predictions: Trenton MOVES -- A preliminary analysis of an interesting MOVES-style proof-of-market deployment -- So, what are the real opportunities quantitatively? ...”
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164Published 2018Table of Contents: “...Note continued: 11.2.1.2.Other methods for linear quantile regression with measurement errors / Ying Wei -- 11.2.2.Nonparametric and semiparametric quantile regression model with measurement errors / Ying Wei -- 11.3.Quantile regression with missing data / Ying Wei -- 11.3.1.Statistical methods handling missing covariates in quantile regression / Ying Wei -- 11.3.1.1.Multiple imputation algorithm / Ying Wei -- 11.3.1.2.Modified MI algorithms / Ying Wei -- 11.3.1.3.EM algorithm / Ying Wei -- 11.3.1.4.IPW algorithms / Ying Wei -- 11.3.2.Statistical methods handling missing outcomes in quantile regression / Ying Wei -- 11.3.2.1.Imputation approaches for missing outcomes / Ying Wei -- 11.3.2.2.Statistical methods for longitudinal dropout / Ying Wei -- 12.1.Multivariate quantiles, and the ordering of Rd, d > or = to 2 / Marc Hallin / Miroslav Siman -- 12.2.Directional approaches / Marc Hallin / Miroslav Siman -- 12.2.1.Projection methods / Marc Hallin / Miroslav Siman...”
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