Non-parametric methods of estimation of type A uncertainty of the environmental noise hazard indices
A control of environmental noise hazards requires estimation of uncertainty of noise indices LDEN, LN. Assessment of the type A standard uncertainty in measurement results - expressed as the standard deviation of the mean, calculated the most often at the assumption of a normal...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute of Fundamental Technological Research Polish Academy of Sciences
2009-01-01
|
| Series: | Archives of Acoustics |
| Online Access: | https://acoustics.ippt.pan.pl/index.php/aa/article/view/580 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | A control of environmental noise hazards requires
estimation of uncertainty of noise indices LDEN, LN. Assessment of the type A
standard uncertainty in measurement results - expressed as the standard
deviation of the mean, calculated the most often at the assumption of a normal
distribution - is significant for the process. Such assumption - in relation to
the noise measurement results - is of a relatively low likelihood. Thus, there
is a need of looking for non-standard procedures of the standard deviation
estimation of the mean of results, without any information of belonging to a
certain class of distribution. The aim of the hereby paper is an indication of
the possibility of using non-parametric estimators of a density function in the
calculation process of the type A standard uncertainty of environmental noise
hazard indices. An attention was directed towards kernel estimators. The origin
of their application, advantages and the method of constructing was described on
the basis of a continuous monitoring of a traffic noise recorded on one of the
main arteries of Kraków in 2004 and 2005. Usefulness of three forms of
estimators, it means: kernel, unbiased and of maximum likelihood, was analysed.
Keywords:acoustic monitoring of environment, analysis of the results, type A
standard uncertainty in measurements, kernel estimator. |
|---|---|
| ISSN: | 0137-5075 2300-262X |