Avoid the perils of using rounded data

2015 ◽  
Vol 115 ◽  
pp. 502-508 ◽  
Author(s):  
Phil J. Borman ◽  
Marion J. Chatfield
Keyword(s):  
2012 ◽  
Vol 51 (1) ◽  
pp. 45-53
Author(s):  
Meihui Guo ◽  
Gen-Liang Li

ABSTRACT Most recorded data of continuous distributions are rounded to the nearest decimal place due to the precision of the recording mechanism. This rounding entails errors in estimation and measurement. In this study, we consider parameter estimation of time series models based on rounded data. The adjusted maximum likelihood estimates in [Stam, A.-Cogger, K. O.: Rounding errors in autoregressive processes, Internat. J. Forecast. 9 (1993), 487-508] are derived theoretically for the first order moving average MA(1) model. Simulations are performed to compare the efficiencies of the adjusted maximum likelihood estimators with other estimators.


2011 ◽  
Vol 53 (4) ◽  
pp. 895-914 ◽  
Author(s):  
Ningning Zhao ◽  
Zhidong Bai
Keyword(s):  

2020 ◽  
Vol 246 (4) ◽  
pp. 565-568
Author(s):  
N. G. Ushakov ◽  
V. G. Ushakov
Keyword(s):  

2019 ◽  
Vol 237 (6) ◽  
pp. 819-825
Author(s):  
S. V. Samsonov ◽  
N. G. Ushakov ◽  
V. G. Ushakov
Keyword(s):  

2011 ◽  
Vol 141 (1) ◽  
pp. 287-292
Author(s):  
Yoichi Nishiyama
Keyword(s):  

1972 ◽  
Vol 14 (3) ◽  
pp. 204-210
Author(s):  
J. A. Lambert
Keyword(s):  

Biometrics ◽  
1979 ◽  
Vol 35 (4) ◽  
pp. 873 ◽  
Author(s):  
M. D. Nicholson
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document