## Abstract This paper investigates Bayesian forecasts for some cointegrated time series data. Suppose data are derived from some cointegrated model, but, an unrestricted vector autoregressive model, without including cointegrated conditions, is fitted; the implication of using an incorrect model w
A bayesian forecasting model for sequential bidding
β Scribed by D. N. Attwell; J. Q. Smith
- Publisher
- John Wiley and Sons
- Year
- 1991
- Tongue
- English
- Weight
- 748 KB
- Volume
- 10
- Category
- Article
- ISSN
- 0277-6693
No coin nor oath required. For personal study only.
β¦ Synopsis
In this paper we consider the problem facing a company in selecting the values of bids to submit on a sequence of contracts put out to tender. A simple-to-implement Bayesian forecasting model is presented, based on a steady Dirichlet process whose states are indexed by the possible bid decisions open to the company. The model gives an explicit algorithm for calculating the state probabilities, needing only data on the lowest bid made by the company's competitors. The flexibility of the basic model makes it a potentially powerful forecasting system for use by companies bidding for contracts.
KEY WORDS Competitive bidding Gates' formula Dirichlet model
Bayesian forecasting Probability elicitation
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