Mean Squared Error and Comparing Models

نویسنده

  • Cedric E. Ginestet
چکیده

This criterion should be contrasted with the RSS encountered earlier in the course. The RSS pertains to model estimation, since we are already assuming a given model for some particular data set; and it suffices to estimate the specific values of our estimators for the unknown parameters. The MSE combines the previous two criteria, on the unbiasedness and the variance of β̂, through the following decomposition:

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

Presenting a new equation for estimation of daily coefficient of evaporation pan using Gene Expression Programming and comparing it with experimental methods (Case Study: Birjand Plain)

One of the most important componenets of water management in farms is estimating crops’ exact amount of  evapotranspiration (water need). The FAO-Penman-Montheis (FPM) method is a standard method to evaluate other techniques which are used for easy calculation of potential evapotranspiration, when lysimeter datasheets are not available. This study was carried out based on 18 years’ climatic dat...

متن کامل

Regression Trees for Longitudinal and Multiresponse Data

Previous algorithms for constructing regression tree models for longitudinal and multiresponse data have mostly followed the CART approach. Consequently, they inherit the same selection biases and computational difficulties as CART. We propose an alternative, based on the GUIDE approach, that treats each longitudinal data series as a curve and uses chi-squared tests of the residual curve patter...

متن کامل

Forecast Evaluation of Small Nested Model Sets

We propose two new procedures for comparing the mean squared prediction error (MSPE) of a benchmark model to the MSPEs of a small set of alternative models that nest the benchmark. Our procedures compare the benchmark to all the alternative models simultaneously rather than sequentially, and do not require bootstrapping. Both procedures adjust MSPE differences in accordance with Clark and West ...

متن کامل

Using Machine Learning ARIMA to Predict the Price of Cryptocurrencies

The increasing volatility in pricing and growing potential for profit in digital currency have made predicting the price of cryptocurrency a very attractive research topic. Several studies have already been conducted using various machine-learning models to predict crypto currency prices. This study presented in this paper applied a classic Autoregressive Integrated Moving Average(ARIMA) model ...

متن کامل

Estimating a Bounded Normal Mean Relative to Squared Error Loss Function

Let be a random sample from a normal distribution with unknown mean and known variance The usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. In many practical situations, is known in advance to lie in an interval, say for some In this case, the maximum likelihood estimator...

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 2013