Author: C. Peter Rydell
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 111
Book Description
The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Personnel
Author: C. Peter Rydell
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 111
Book Description
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 111
Book Description
The Benchmark Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel
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.
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.
Time Series Models for Predicting Monthly Losses of Air Force Enlisted Personnel
Author: Marygail K. Brauner
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 108
Book Description
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 108
Book Description
The Robust Separation Projection Method for Predicting Monthly Losses of Air Force Enlisted Personnel
Author: Marygail K. Brauner
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 74
Book Description
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 74
Book Description
Short-term Aggregate Model for Projecting Air Force Enlisted Personnel (SAM)
Author: C. Peter Rydell
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 168
Book Description
Publisher:
ISBN:
Category : Time-series analysis
Languages : en
Pages : 168
Book Description
A Rand Note
Government Reports Annual Index
Author:
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 1200
Book Description
Sections 1-2. Keyword Index.--Section 3. Personal author index.--Section 4. Corporate author index.-- Section 5. Contract/grant number index, NTIS order/report number index 1-E.--Section 6. NTIS order/report number index F-Z.
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 1200
Book Description
Sections 1-2. Keyword Index.--Section 3. Personal author index.--Section 4. Corporate author index.-- Section 5. Contract/grant number index, NTIS order/report number index 1-E.--Section 6. NTIS order/report number index F-Z.
Rand
Author: Rand Corporation
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 124
Book Description
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 124
Book Description