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Though measurement instruments and methods have their natural precision limits, long term monitoring, which is so importantfor environmental studies, requires to set up and maintaincertain standards regarding precision. The elementaryrequirement is to produce measurements with a prescribed numberof valid digits. If the technology further develops and allowsto increase the number of valid digits, the change should bedocumented. In this paper we discuss a simple procedure for validity assessment of the last digits of data in a data base.It may be useful for both calibration control of an instrumentas well as for preliminary data analysis in scientific studies.The procedure utilizes the assumption that, under normalconditions, the last digits of the observed data can usually beconsidered as uniformly distributed random numbers. Failures ordeliberate changes in the observation mechanism can be detectedif particular digits occur more frequently than the others. Thedecision about proper representations of the last digits is doneby means of the familiar chi-square statistics.  相似文献   
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The objective of this study is to decide if chemical concentrations measured during 1988-1997in precipitation by the Canadian Air and Precipitation Monitoring Network (CAPMoN) indicate changes in the annual patterns. The inference is based on SO4, NO3, Cl,NH4, Na, Ca and K concentrations monitored daily with the rain water acidity pH. By pattern is understood the probability distribution of the annual sample at a particular location. Most of the annual data can be well described by means of a linear regression model with second order polynomial trend and autocorrelated noise. Statistical analysis based on the model shows luck of systematic significant year to year increases or declines of the concentrations.  相似文献   
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This paper describes a statistical analysis of wet sulfate deposition data sampled by the Canadian Air and Precipitation Monitoring Network (CAPMoN) since 1988 till 1997. The goal of the investigation is to detect presence of prevailing significant changes in the probability distribution of annual samples collected by the network at each site. The considerations are based on a first order autoregression model with second order polynomial trend and methods used for analysis of variance and multiple comparison. Unlike studies suggesting existence of long term trends in the data, methods applied here indicate absence of any systematic changes in the observed annual concentration patterns at most of the sites.  相似文献   
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