Government of Canada

About: Government of Canada is a government organization based out in Ottawa, Ontario, Canada. It is known for research contribution in the topics: Monetary policy & Debt. The organization has 796 authors who have published 886 publications receiving 21366 citations. The organization is also known as: federal government of Canada & Her Majesty's Government.

Retrospective Evaluation of Preseason Forecasting Models for Pink Salmon

Abstract: Models for making preseason forecasts of adult abundance are an important component of the management of many stocks of Pacific salmon Oncorhynchus spp. Reliable forecasts could increase both the profits from fisheries and the probability of achieving conservation and other management targets. However, the predictive performance of salmon forecasting models is generally poor, in part because of the high variability in salmon survival rates. To improve the accuracy of forecasts, we retrospectively evaluated the performance of eight preseason forecasting models for 43 stocks of pink salmon O. gorbuscha over a total of 783 stock-years. The results indicate that no single forecasting model was consistently the most accurate. Nevertheless, across the 43 stocks we found that two naive time series models (i.e., those without explicitly modeled mechanisms) most frequently performed best based on mean raw error, mean absolute error, mean percent error, and root mean square error for forecasts of total adu...

Using Low Frequency Information for Predicting High Frequency Variables

Abstract: We analyze how to incorporate low frequency information in models for predicting high frequency variables. In doing so, we introduce a new model, the reverse unrestricted MIDAS (RU-MIDAS), which has a periodic structure but can be estimated by simple least squares methods and used to produce forecasts of high frequency variables that also incorporate low frequency information. We compare this model with two versions of the mixed frequency VAR, which so far had been only applied to study the reverse problem, that is, using the high frequency information for predicting low frequency variables. We then implement a simulation study to evaluate the relative forecasting ability of the alternative models in finite samples. Finally, we conduct several empirical applications to assess the relevance of quarterly survey data for forecasting a set of monthly macroeconomic indicators. Overall, it turns out that low frequency information is important, particularly so when it is just released.

Change Detection with Compact Polarimetric SAR for Monitoring Wetlands

Abstract: . Compact polarimetric synthetic aperture radar (SAR) architecture is an SAR configuration that consists of transmitting a single circular polarization (left or right) or a 45° oriented linear signal while receiving two linear polarizations, horizontal and vertical. In this study we investigate the potential of the compact polarimetric SAR mode for wetland monitoring applications. Whitewater Lake located in Manitoba, Canada, is selected as a case study where simulated compact polarimetric SAR data are obtained using RADARSAT-2 Fine Quad-POL SAR images. The ability of the compact polarimetric data to monitor wetlands using the Wishart-Chernoff distance is studied and compared to the results obtained using fully polarimetric data. Results of this study show that compact polarimetry provides monitoring capabilities for wetlands. Promising change detection mapping results based on the compact polarimetric coherency matrices are obtained using the Wishart-Chernoff distance. This could be useful for fla...

On the Robustness of Some Tests of Significance in Sampling from a Compound Normal Population

Abstract: This article deals with the behavior of some tests of significance in sampling from a mixture of two normal populations. Three particular cases are considered: (i) one-sample t-test; (ii) analysis-of-variance test for the equality of two or more means and (iii) analysis-of-variance test for the regression coefficient being zero. The assessment is based on the actual value of α (level of significance) when the nominal α is .05.