Time Series Models for Predicting Monthly Losses of Air Force Enlisted Personnel

Time Series Models for Predicting Monthly Losses of Air Force Enlisted Personnel PDF Author: Marygail K. Brauner
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 108

Book Description


The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel

The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel PDF Author: C. Peter Rydell
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 136

Book Description
RAND is helping to design an Enlisted Force Management System (EFMS) for the Air Force. The efms is a decision support system designed to assist managers of the enlisted force in setting and meeting force targets. The system contains computer models that project the force resulting from given management actions, so actions that meet targets can be found. Some of those models analyze separate job specialties (disaggregate models) and others analyze the total enlisted force across all specialties (aggregate models); some models make annual projections (middle-term models) and others monthly projections. The Short-Term Aggregate Inventory Projection Model (SAM) is the component of the EFMS that makes monthly projections (for the rest of the current fiscal year) of the aggregate enlisted force.

BENCHMARK SEPARATION PROJECT METHOD FOR PREDICTING MONTHLY LOSSES OF AIR FORCE ENLISTED PERSONNEL.

BENCHMARK SEPARATION PROJECT METHOD FOR PREDICTING MONTHLY LOSSES OF AIR FORCE ENLISTED PERSONNEL. PDF Author: Rand Corporation
Publisher:
ISBN:
Category :
Languages : en
Pages : 100

Book Description


Short-term Aggregate Model for Projecting Air Force Enlisted Personnel (SAM)

Short-term Aggregate Model for Projecting Air Force Enlisted Personnel (SAM) PDF Author: C. Peter Rydell
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 168

Book Description


The Robust Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel

The Robust Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel PDF Author: Marygail K. Brauner
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 74

Book Description


The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Personnel

The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Personnel PDF Author: C. Peter Rydell
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 111

Book Description


Middle-term Disaggregate Loss Model Test and Evaluation

Middle-term Disaggregate Loss Model Test and Evaluation PDF Author: Allan F. Abrahamse
Publisher:
ISBN:
Category :
Languages : en
Pages : 120

Book Description
"Air Force planners use inventory projection models (IPMs) to predict how an initial inventory of airmen will look in the future. Such IPMs contain loss models that estimate how many members of the initial inventory leave the service during the period in question. Middle-term disaggregate loss models predict annual loss rates, by Air Force Specialty Code (AFSC) and certain other factors. In 1983, as part of a larger effort to develop a new Enlisted Force Management System (EFMS) for the Air Force (Carter et al., 1983), RAND began developing a set of middle-term disaggregate loss models for use in the EFMS's Middle-Term Disaggregate IPM. This document describes the testing and evaluation of these loss models. The purpose of the T & E exercise was to identify problems with the models so that the problems could be fixed before the models were implemented in the EFMS. This document describes the testing and evaluation of a set of equations that predict airman loss and reenlistment behavior. The equations were developed for use in the Air Force's Enlisted Force Management System (EFMS. The conceptual design of the EFMS includes a variety of loss models distinguished by the time horizon of their predictions (short-, middle-, or long-term) and whether such predictions are disaggregated by occupational specialty. This document concerns the middle-term disaggregate loss model, which predicts annual loss rates by Air Force Specialty code (AFSC). Its predictions are designed to be most accurate between one and four years into the future."--DTIC

Confirmation Hearings on Federal Appointments

Confirmation Hearings on Federal Appointments PDF Author: United States. Congress. Senate. Committee on the Judiciary
Publisher:
ISBN:
Category : Law
Languages : en
Pages : 1178

Book Description


Rand

Rand PDF Author: Rand Corporation
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 124

Book Description


Government Reports Annual Index

Government Reports Annual Index PDF Author:
Publisher:
ISBN:
Category : Government reports announcements & index
Languages : en
Pages : 1832

Book Description