Hardware Optimized Approximate Adder with Normal Error Distribution

AbstractIn this paper, we suggest new cointegration tests that can become more powerful in the presence of non-normal errors. Non-normal errors will not pose a problem in usual cointegration tests even when they are ignored. However, we show that they can become useful sources to improve the power of the tests when we use the “residual augmented least squares” (RALS) procedure to make use of nonlinear moment conditions driven by non-normal errors. The suggested testing procedure is easy to implement and it does not require any non-linear estimation techniques. We can exploit the information on the non-normal error distribution that is already available but ignored in the usual cointegration tests. Our simulation results show significant power gains over existing cointegration tests in the presence of non-normal errors.

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Appendix D: Normal Error Distribution Curve and Other Statistical Tables

Adjustment Computations ◽

10.1002/9780470586266.app04 ◽

2010 ◽

pp. 586-605

Keyword(s):

Distribution Curve ◽

Error Distribution ◽

Normal Error ◽

Normal Error Distribution

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An Approximate Adder With a Near-Normal Error Distribution: Design, Error Analysis and Practical Application

IEEE Access ◽

10.1109/access.2020.3047651 ◽

2021 ◽

Vol 9 ◽

pp. 4518-4530

Author(s):

Padmanabhan Balasubramanian ◽

Raunaq Nayar ◽

Douglas L. Maskell ◽

Nikos E. Mastorakis

Keyword(s):

Error Analysis ◽

Error Distribution ◽

Practical Application ◽

Design Error ◽

Normal Error ◽

Normal Error Distribution

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Appendix D: Normal Error Distribution Curve and Other Statistical Tables

Adjustment Computations ◽

10.1002/9780470121498.app4 ◽

2007 ◽

pp. 556-575

Keyword(s):

Distribution Curve ◽

Error Distribution ◽

Normal Error ◽

Normal Error Distribution

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Modeling and Estimating Volatility of Day-Ahead Electricity Prices

Mathematics ◽

10.3390/math9070750 ◽

2021 ◽

Vol 9 (7) ◽

pp. 750

Author(s):

Sherzod N. Tashpulatov

Keyword(s):

Heavy Tails ◽

Price Level ◽

Power Market ◽

Error Distribution ◽

Electricity Prices ◽

Volatility Model ◽

Generalized Error Distribution ◽

Student’S T ◽

The Uk ◽

The Impact

We model day-ahead electricity prices of the UK power market using skew generalized error distribution. This distribution allows us to take into account the features of asymmetry, heavy tails, and a peak higher than in normal or Student’s t distributions. The adequacy of the estimated volatility model is verified using various tests and criteria. A correctly specified volatility model can be used for analyzing the impact of reforms or other events. We find that, after the start of the COVID-19 pandemic, price level and volatility increased.

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Experiment Research on the Temperature Field and Thermal Error Distribution of NC Grinding Machine

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.76-78.61 ◽

2009 ◽

Vol 76-78 ◽

pp. 61-66

Author(s):

Ya Dong Gong ◽

Yan Guang Bai ◽

Yue Ming Liu ◽

Jian Qiu

Keyword(s):

Mathematical Model ◽

Temperature Field ◽

Infrared Camera ◽

Thermal Error ◽

Error Distribution ◽

Measurement Technology ◽

Actual Error ◽

Grinding Machine ◽

The Mathematical Model ◽

Nc Grinding

With the help of the infrared camera temperature measurement technology, the systemic theoretical analysis and experimental research for temperature field and thermal error distribution in NC grinding machine is provided. Two different situations for temperature field and thermal error distribution are respectively measured while the free and loaded grinding by the new measurement method. The mathematical model of thermal error is built, and it shows that the actual error and the forecasted error from thermal error mathematical model have good comparability.

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