Accuracy of Numerical Solution to Dynamic Programming Models

Dynamic programming models with continuous state and control variables are solved approximately using numerical methods in most applications. We develop a method for measuring the accuracy of numerical solution of stochastic dynamic programming models. Using this method, we compare the accuracy of various interpolation schemes. As expected, the results show that the accuracy improves as number of nodes is increased. Comparison of Chebyshev and linear spline indicates that the linear spline may give higher maximum absolute error than Chebyshev, however, the overall performance of spline interpolation is better than Chebyshev interpolation for non-smooth functions. Two-stage grid search method of optimization is developed and examined with accuracy analysis. The results show that this method is more efficient and accurate. Accuracy is also examined by allocating a different number of nodes for each dimension. The results show that a change in node configuration may yield a more efficient and accurate solution.Research Methods/ Statistical Methods,

B844: Checklist of the Vascular Plants of Maine Third Revision

This is the third revision of the Checklist of Vascular Plants of Maine. Like its predecessors, it lists all ferns and related plants, conifers, and flowering plants native and naturalized in Maine and records their county-level distribution in the state. The first Check- list (Ogden et al. 1948) was based on specimens in herbaria at the University of Maine (hereafter referred to as MAINE), Portland Society of Natural History, New England Botanical Club, Gray Herbarium of Harvard University, and the private collection of Glen D. Chamberlain of Presque Isle, Maine (now part of MAINE). Bean et al. (1966) revised the checklist to include additions to the flora and update the nomenclature to follow Fernald (1950). Richards et al. (1983) added many new state and county records in the second revision. The purpose of this revision is twofold. First, we have included many new county and state records. Since Richards et al. (1983) there has been considerable collecting in Maine, much of it directed at searching for new state and county records in relatively neglected regions of the state. Second, there have been numerous changes in the scientific names of Maine plants since Fernald (1950), the nomenclatural basis of Richards et al. (1983). We have largely followed Kartesz\u27s (1994) nomenclature (see Taxonomy and Nomenclature section). Recent work on rare plants and establishment of an official list of endangered and threatened plants in Maine (Dibble et al. 1989; Maine State Planning Office 1990) also motivate updating the known distribution and taxonomy of Maine\u27s flora.https://digitalcommons.library.umaine.edu/aes_bulletin/1121/thumbnail.jp

Drought Severity and Frequency Analysis Aided by Spectral and Meteorological Indices in the Kurdistan Region of Iraq

In the past two decades, severe drought has been a recurrent problem in Iraq due in part to climate change. Additionally, the catastrophic drop in the discharge of the Tigris and Euphrates rivers and their tributaries has aggravated the drought situation in Iraq, which was formerly one of the most water-rich nations in the Middle East. The Kurdistan Region of Iraq (KRI) also has catastrophic drought conditions. This study analyzed a Landsat time-series dataset from 1998 to 2021 to determine the drought severity status in the KRI. The Modified Soil-Adjusted Vegetation Index (MSAVI2) and Normalized Difference Water Index (NDWI) were used as spectral-based drought indices to evaluate the severity of the drought and study the changes in vegetative cover, water bodies, and precipitation. The Standardized Precipitation Index (SPI) and the Spatial Coefficient of Variation (CV) were used as meteorologically based drought indices. According to this study, the study area had precipitation deficits and severe droughts in 2000, 2008, 2012, and 2021. The MSAVI2 results indicated that the vegetative cover decreased by 36.4%, 39.8%, and 46.3% in 2000, 2008, and 2012, respectively. The SPI’s results indicated that the KRI experienced droughts in 1999, 2000, 2008, 2009, 2012, and 2021, while the southeastern part of the KRI was most affected by drought in 2008. In 2012, the KRI’s western and southern parts were also considerably affected by drought. Furthermore, Lake Dukan (LD), which lost 63.9% of its surface area in 1999, experienced the most remarkable shrinkage among water bodies. Analysis of the geographic distribution of the CV of annual precipitation indicated that the northeastern parts, which get much more precipitation, had less spatial rainfall variability and more uniform distribution throughout the year than other areas. Moreover, the southwest parts exhibited a higher fluctuation in annual spatial variation. There was a statistically significant positive correlation between MSAVI2, SPI, NDWI, and agricultural yield-based vegetation cover. The results also revealed that low precipitation rates are always associated with declining crop yields and LD shrinkage. These findings may be concluded to provide policymakers in the KRI with a scientific foundation for agricultural preservation and drought mitigation

Registered Ship Notes

https://digitalmaine.com/blue_hill_documents/1179/thumbnail.jp

Accuracy of Numerical Solution to Dynamic Programming Models

Dynamic programming models with continuous state and control variables are solved approximately using numerical methods in most applications. We develop a method for measuring the accuracy of numerical solution of stochastic dynamic programming models. Using this method, we compare the accuracy of various interpolation schemes. As expected, the results show that the accuracy improves as number of nodes is increased. Comparison of Chebyshev and linear spline indicates that the linear spline may give higher maximum absolute error than Chebyshev, however, the overall performance of spline interpolation is better than Chebyshev interpolation for non-smooth functions. Two-stage grid search method of optimization is developed and examined with accuracy analysis. The results show that this method is more efficient and accurate. Accuracy is also examined by allocating a different number of nodes for each dimension. The results show that a change in node configuration may yield a more efficient and accurate solution

A Stochastic Dynamic Programming Analysis of Farmland Investment and Financial Management

"This paper develops a multiperiod investment portfolio model that includes risky farmland, risky and risk-free nonfarm assets, and debt financing on farmland in the presence of transaction costs and credit constraints. The model is formulated as a stochastic continuous-state dynamic programming problem, and is solved numerically for Southwestern Minnesota, USA. Results show that optimal investment decisions are dynamic and take into account the future decisions due to uncertainty, partial irreversibility, and the option to wait. The optimal policy includes ranges of inaction, states where the optimal policy in the current year is to wait. The risk-averse farmer makes a lower investment in risky farmland reflecting risk-avoiding behavior. We find that, in addition to risk aversion, the length of the planning horizon affects risk-avoiding behavior in investment decisions. In contrast to a static model, changes in the riskiness of returns affect optimal investment decisions even when the decision maker is risk neutral. Finally, we find that higher debt financing on farmland is optimal when risky nonfarm assets can be included in the optimal investment portfolio and that the probability of exiting farming increases with the risky nonfarm investment." Copyright (c) 2009 Canadian Agricultural Economics Society.