How Does the Persons per Household Variable Affect Population Estimation and How to Measure It

A presentation on statistical methods for estimating persons per household (PPH) in New Mexico. The author presents a brief overview of PPH concepts, the effects of the PPH variable in population estimation, components that affect PPH, and selection and validation of a model for estimating PPH. He outlines his methodology: regression methods; stepwise selection, using SAS; Bayesian probability testing with WinBUGS; and validation of the model. Illustrated with charts and tables

Spatial Demography as a Method for Population Estimation: Addressing Census Bureau Under-estimation of New Mexico\u27s Populations Using GIS Technologies

This article discusses the census undercount problem in New Mexico and plans to remedy the situation by using GIS technology to improve the quality and accuracy of local population estimates. It describes the geospatial demographic estimation modeling methods used by researchers at the UNM Bureau of Business and Economic Research-Population Estimates Program (BBER-PEP) to reduce undercount. The article also briefly describes future population studies planned by BBER-PEP using GIS technology. Illustrated with maps and tables

A Stochastic Version of the Brass PF Ratio Adjustment of Age-Specific Fertility Schedules

Estimates of age-specific fertility rates based on survey data are known to suffer down-bias associated with incomplete reporting. Previously, William Brass (1964, 1965, 1968) proposed a series of adjustments of such data to reflect more appropriate levels of fertility through comparison with data on children-ever-born by age, a measure of cohort-specific cumulative fertility. His now widely-used Parity/Fertility or PF ratio method makes a number of strong assumptions, which have been the focus of an extended discussion in the literature on indirect estimation. However, while it is clear that the measures used in making adjusted age-specific fertility estimates with this method are captured with statistical uncertainty, little discussion of the nature of this uncertainty around PF-ratio based estimates of fertility has been entertained in the literature. Since both age-specific risk of childbearing and cumulative parity (children ever born) are measured with statistical uncertainty, an unknown credibility interval must surround every PF ratio-based estimate. Using the standard approach, this is unknown, limiting the ability to make statistical comparisons of fertility between groups or to understand stochasticity in population dynamics. This paper makes use of approaches applied to similar problems in engineering, the natural sciences, and decision analysis—often discussed under the title of uncertainty analysis or stochastic modeling—to characterize this uncertainty and to present a new method for making PF ratio-based fertility estimates with 95 percent uncertainty intervals. The implications for demographic analysis, between-group comparisons of fertility, and the field of statistical demography are explored

MCTS/EA hybrid GVGAI players and game difficulty estimation

© 2016 IEEE. In the General Video Game Playing competitions of the last years, Monte-Carlo tree search as well as Evolutionary Algorithm based controllers have been successful. However, both approaches have certain weaknesses, suggesting that certain hybrids could outperform both. We envision and experimentally compare several types of hybrids of two basic approaches, as well as some possible extensions. In order to achieve a better understanding of the games in the competition and the strength and weaknesses of different controllers, we also propose and apply a novel game difficulty estimation scheme based on several observable game characteristics

Cytosolic Glucose-6-Phosphate Dehydrogenase Is Involved in Seed Germination and Root Growth Under Salinity in Arabidopsis

Glucose-6-phosphate dehydrogenase (G6PDH or G6PD) is the key regulatory enzyme in the oxidative pentose phosphate pathway (OPPP). The cytosolic isoforms including G6PD5 and G6PD6 account for the major part of the G6PD total activity in plant cells. Here, we characterized the Arabidopsis single null mutant g6pd5 and g6pd6 and double mutant g6pd5/6. Compared to wild type, the mutant seeds showed a reduced germination rate and root elongation under salt stress. The seeds and seedlings lacking G6PD5 and G6PD6 accumulate more reactive oxygen species (ROS) than the wild type under salt stress. Cytosolic G6PD (cy-G6PD) affected the expression of NADPH oxidases and the G6PD enzymatic activities in the mutant atrbohD/F, in which the NADPH oxidases genes are disrupted by T-DNA insertion and generation of ROS is inhibited, were lower than that in the wild type. The NADPH level in mutants was decreased under salt stress. In addition, we found that G6PD5 and G6PD6 affected the activities and transcript levels of various antioxidant enzymes in response to salt stress, especially the ascorbate peroxidase and glutathione reductase. Exogenous application of ascorbate acid and glutathione rescued the seed and root phenotype of g6pd5/6 under salt stress. Interestingly, the cytosolic G6PD negatively modulated the NaCl-blocked primary root growth under salt stress in the root meristem and elongation zone

Coordinated Population Forecast for Lane County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065

Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Lane County’s total population has grown steadily since 2000; with an average annual growth rate of just under one percent between 2000 and 2010 (Figure 1); however some of its sub-areas experienced more rapid population growth during the 2000s. Veneta and Creswell posted the highest average annual growth rates at 5.2 and 3.1 percent, respectively, during the 2000 to 2010 period. Lane County’s positive population growth in the 2000s was the direct result of substantial net inmigration and in the early years, natural increase. Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to slower growth in births. The more rapid growth in deaths relative to that of births caused natural increase—the difference between births and deaths—to shrink between 2007 and 2012. Since 2012, net in-migration has outpaced natural increase, driving rising population growth rates. Total population in Lane County as a whole as well as within many of its sub-areas is forecast to grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035), relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to declining natural increase (births minus deaths). As natural increase declines and eventually becomes natural decrease, population growth is expected to become increasingly reliant on net in-migration. Even so, Lane County’s total population is forecast to increase by nearly 67,300 over the next 20 years (2015-2035) and by nearly 152,400 over the entire 50 year forecast period (2015-2065). Sub-areas that showed strong population growth in the 2000s are expected to experience similar rates of population growth during the forecast period

Coordinated Population Forecast for Deschutes County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065

Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Deschutes County’s total population has grown rapidly since 2000, with an average annual growth rate of more than three percent between 2000 and 2010 (Figure 1); in addition, most of its sub-areas experienced even more rapid population growth during the 2000s. Sisters and La Pine posted the highest average annual growth rates at 7.8 and 6.3 percent, respectively, during the 2000 to 2010 period. Deschutes County’s positive population growth in the 2000s was the direct result of substantial net inmigration and steady natural increase (i.e., more births than deaths). Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to slower growth in births. The more rapid growth in deaths relative to that of births caused natural increase—the difference between births and deaths—to shrink between 2007 and 2014. While net in-migration and steady natural increase contributed to population growth during the early and middle years of the last decade, it is clear that in more recent years (i.e., 2010 to 2014) net inmigration played the most prominent role in population growth. Total population in Deschutes County as a whole as well as within its sub-areas is forecast to grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035), relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to natural decrease (more deaths than births). As natural decrease occurs, population growth will become increasingly reliant on net in-migration. Even so, Deschutes County’s total population is forecast to increase by more than 78,000 over the next 20 years (2015-2035) and by more than 186,000 over the entire 50 year forecast period (2015-2065). Sub-areas that showed strong population growth in the 2000s are expected to experience similar rates of population growth during the forecast period

Coordinated Population Forecast for Josephine County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2015-2065

Different growth patterns occur in different parts of the county and these local trends within the UGBs and the area outside UGBs collectively influence population growth rates for the county as a whole. Josephine County’s total population as a whole has grown slowly since 2000; with an average annual growth rate of less than one percent between 2000 and 2010 (Figure 1); however some of its sub-areas experienced more rapid population growth during the 2000s. Grants Pass and Cave Junction posted average annual growth rates at 2.1 and 1.6 percent, respectively, during the 2000 to 2010 period. Josephine County’s positive population growth in the 2000s was the result of substantial net inmigration. Meanwhile an aging population not only led to an increase in deaths, but also resulted in a smaller proportion of women in their childbearing years. This along with more women choosing to have fewer children and have them at older ages has led to slow growth in the number of births. The growing number of deaths and shrinking number of births led to natural decrease—more deaths than births—in every year from 2000 to 2014. While net in-migration outweighed natural decrease during the early and middle years of the last decade, the gap between these two numbers shrank during the later years— bringing population decline in 2012. Since 2012 net in-migration has increased, driving population increase for 2013 and 2014. Total population in Josephine County as a whole as well as within its sub-areas will likely grow at a slightly faster pace in the first 20 years of the forecast period (2015 to 2035) relative to the last 30 years (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to lead to natural decrease (more deaths than births). As natural decrease occurs over time population growth is expected to become increasingly reliant on net in-migration. Even so, Josephine County’s total population is forecast to increase by more than 16,000 over the next 20 years (2015-2035) and by nearly 38,000 over the entire 50-year forecast period (2015-2065). Subareas that showed strong population growth in the 2000s are expected to experience similar rates of population growth during the forecast period

Coordinated Population Forecast for Umatilla County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2016-2066

Umatilla County’s total population has grown steadily since 2000, with average annual growth rates near one percent between 2000 and 2010 (Figure 1); however, some of its sub-areas experienced more rapid population growth during the 2000s. Hermiston, the most populous UGB, and Umatilla UGB posted the highest average annual growth rates at 2.1 and 2.8 percent, respectively, during the 2000 to 2010 period. Umatilla County’s positive population growth in the 2000s was the result of a steady natural increase and periods of substantial net in-migration. A larger number of births relative to deaths led to a natural increase (more births than deaths) in every year from 2000 to 2015 (Figure 12). While net in-migration fluctuated dramatically during the early and middle years of the last decade, the number of in-migrants has been slightly more stable during recent years, contributing to a population increase. Even so the natural increase continues to account for most of the population growth. Total population in Umatilla County as a whole as well as within its sub-areas will likely grow at a slightly faster pace in the near-term (2016 to 2035) compared to the long-term (2035-2066) (Figure 1). The tapering of growth rates is driven by an aging population—a demographic trend which is expected to contribute to an increase in deaths. Even so, natural increase is expected to persist, combining with steady in-migration for continued strong population growth. Umatilla County’s total population is forecast to increase by nearly 13,300 over the next 19 years (2016- 2035) and by close to 36,800 over the entire 50-year forecast period (2016-2066). All sub-areas are expected to experience population growth during the forecast period

Coordinated Population Forecast for Union County, its Urban Growth Boundaries (UGB), and Area Outside UGBs 2016-2066

Union County’s total population has grown slowly since 2000, with an average annual growth rate of half percent between 2000 and 2010 (Figure 1). However, some of its sub-areas experienced more rapid population growth during the 2000s. Summerville posted the highest average annual growth rate of 1.4 percent, and Imbler and Union were close behind with average annual growth rates of about 1.2 percent each. Union County’s positive population growth in the 2000s was the combined result of a consistent natural increase and a net in-migration. The larger number of births relative to deaths has led to a natural increase (more births than deaths) in every year from 2000 to 2015 (Figure 12). While net in-migration fluctuated dramatically during the early years of the last decade, the number of in-migrants has been slightly more stable during recent years, accounting for the majority of Union County’s population increase. Total population in Union County as a whole as well as within some of its sub-areas will likely grow at a slightly faster pace in the nearer-term (2016 to 2035) compared to the longer-term (Figure 1). The tapering of growth rates is largely driven by an aging population—a demographic trend which is expected to contribute to natural decrease (more deaths than births). As natural decrease occurs, population growth will become increasingly reliant on net in-migration. Steady increase in net in-migration is expected to offset the growing natural decrease, leading to relatively steady population growth over the forecast period. However, an aging population is expected to not only lead to an increase in deaths, but a smaller proportion of women in their childbearing years will likely result in a long-term stabilization in the number of births