Networks of ambient monitoring stations are used to monitor environmental pollution fields such as those for acid rain and air pollution. Such stations provide regular measurements of pollutant concentrations. The networks are established for a variety of purposes at various times so often several stations measuring different subsets of pollutant concentrations can be found in compact geographical regions. The problem of statistically combining these disparate information sources into a single 'network' then arises. Capitalizing on the efficiencies so achieved can then lead to the secondary problem of extending this network. The subject of this paper is a set of 31 air pollution monitoring stations in southern Ontario. Each of these regularly measures a particular subset of ionic sulphate, sulphite, nitrite and ozone. However, this subset varies from station to station. For example only two stations measure all four. Some measure just one. We describe a Bayesian framework for integrating the measurements of these stations to yield a spatial predictive distribution for unmonitored sites and unmeasured concentrations at existing stations. Furthermore we show how this network can be extended by using an entropy maximization criterion. The methods assume that the multivariate response field being measured has a joint Gaussian distribution conditional on its mean and covariance function. A conjugate prior is used for these parameters, some of its hyperparameters being fitted empirically. 相似文献
In this paper, we propose the hard thresholding regression (HTR) for estimating high‐dimensional sparse linear regression models. HTR uses a two‐stage convex algorithm to approximate the ?0‐penalized regression: The first stage calculates a coarse initial estimator, and the second stage identifies the oracle estimator by borrowing information from the first one. Theoretically, the HTR estimator achieves the strong oracle property over a wide range of regularization parameters. Numerical examples and a real data example lend further support to our proposed methodology. 相似文献
This paper examines the effects of exchange rate depreciation to the U.S. economy in a factor‐augmented vector autoregression model using monthly data of 148 variables for the post–Bretton Woods period of 1973–2017. Exchange rate shock is identified to reflect exogenous disturbances to the foreign exchange market, and movements in exchange rate that are not accounted for by changes in the U.S. monetary policy. We find that depreciation is expansionary and inflationary to the broad U.S. economy, the current account improves over time conforming to the J‐curve theory, and monetary policy is leaning against the wind. (JEL E3, E5, F31, F32, F41) 相似文献
Objective: The objective of this study is to investigate the impact of metabolic status on associations of serum vitamin D with hypogonadism and lower urinary tract symptoms (LUTS)/benign prostatic hyperplasia (BPH).
Patients and methods: A total of 612 men underwent physical examination, biochemical/hormonal blood testing, and transrectal prostate ultrasound. Moreover, the subjects filled out standard questionnaires for identification and grading of LUTS and hypogonadism symptoms. Parameters were statistically compared with independent t-tests and correlation analyses.
Results: Vitamin D levels positively correlated with total testosterone (TT) but not with prostate volume or International Prostate Symptom Score (IPSS). Patients with metabolic syndrome had significantly lower vitamin D levels, which were not correlated with TT, prostate volume, or IPSS. However, vitamin D was positively correlated with TT, and negatively correlated with prostate volume and quality-of-life IPSS in subjects without metabolic syndrome.
Conclusion: The clinical usefulness of vitamin D for treatment of hypogonadism or LUTS/BPH varies according to metabolic status. 相似文献