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We use a form of small area estimation in which survey data is carefully modelled, and the parameter estimates applied to national, small area administrative data. As a result we can produce a detailed map for the survey target variable which is of great value in marketing.

Predictive analytics in manufacturing uses models extracted from historical order and production related records to support the optimization of manufacturing processes. For instance, forecasting the overall amount of incoming orders is crucial for a) properly scheduling and sizing raw material and part orders and b) configuring processes as e.g. final assembly or testing. Loosely based on a specific subproblem in one of our ongoing R&D projects, this howto showcases the process of building an order amount predictor in R.

Pairs Trading with R

October 31, 2011

Entry has been submitted. Publication is conditional upon approval of contestant's employer.

Entry has been submitted. Publication is conditional upon approval of contestant's employer.

Introduction

One of the more important aspects for applying Quality Improvement in Healthcare is the reporting of information on a timely and continuous basis.

Researchers overpromise and undeliver on patient accrual, the time frame in which they plan to obtain the proposed sample sizes for their research studies. It is not uncommon for a researcher to promise to get 100 patients within a year, but then struggle to get even a dozen patients after two years. Slow patient accrual leads to delays in completion of the study or sample size shortfalls or both.

Authors: Patricio Fuenmayor Viteri and Hermann Mena
Emails: patricio.fuenmayor@gmail.com
City: Quito - Ecuador

Introduction

the app shows how to use your own algorithm in r(written in various languages) and compare it with standard clustering algorithms using the visualization tools.