Calibrated Forecasting and Merging

نویسندگان

  • Ehud Kalai
  • Ehud Lehrer
  • Rann Smorodinsky
چکیده

Consider a finite-state stochastic process governed by an unknown objective probability distribution. Observing the system, a forecaster assigns subjective probabilities to future states. The resulting subjective forecast merges to the objective distribution if, with time, the forecasted probabilities converge to the Ž . correct but unknown probabilities. The forecast is calibrated if observed long-run empirical distributions coincide with the forecasted probabilities. This paper links unobserved reliability of forecasts to their observed empirical performance by demonstrating full equivalence between notions of merging and of calibration, and discusses implications of this equivalence for the literature of forecasting and learning. Journal of Economic Literature Classification Numbers: C5, C11, C73, D83. Q 1999 Academic Press

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

CALIBRATED FORECASTING AND MERGING + by

Consider a general finite-state stochastic process governed by an unknown objective probability distribution. Observing the system, a forecaster assigns subjective probabilities to future states. The resulting subjective forecast merges to the objective distribution if, with time, the forecasted probabilities converge to the correct (but unknown) probabilities. The forecast is calibrated if obs...

متن کامل

پیش‌بینی قیمت‌های نقدی گازطبیعی به کمک مدل‌های غیرخطی ناپارامتریک

Developing models for accurate natural gas spot price forecasting is critical because these forecasts are useful in determining a range of regulatory decisions covering both supply and demand of natural gas or for market participants. A price forecasting modeler needs to use trial and error to build mathematical models (such as ANN) for different input combinations. This is very time consuming ...

متن کامل

Short-term Time Series Forecasting with Regression Automata

We present regression automata (RA), which are novel type syntactic models for time series forecasting. Building on top of conventional state-merging algorithms for identifying automata, RA use numeric data in addition to symbolic values and make predictions based on this data in a regression fashion. We apply our model to the problem of hourly wind speed and wind power forecasting. Our results...

متن کامل

Merging multiple precipitation sources for flash flood forecasting

r a 200 .007 : +886 2 tu.edu.t Summary We investigated the effectiveness of combining gauge observations and satellite-derived precipitation on flood forecasting. Two data merging processes were proposed: the first one assumes that the individual precipitation measurement is non-bias, while the second process assumes that each precipitation source is biased and both weighting factor and bias pa...

متن کامل

Does an Efficient Calibrated Forecasting Strategy Exist?

We recall two previously-proposed notions of asymptotic calibration for a forecaster making a sequence of probability predictions. We note that the existence of efficient algorithms for calibrated forecasting holds only in the case of binary outcomes. We pose the question: do there exist such efficient algorithms for the general (non-binary) case? Review of Calibrated Forecasting Glenn Brier, w...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1996