Mimeograph Circular 6

Nearly 150 rural families produced potatoes in the Railbelt area of Alaska during 1952, Only a small proportion of these families were specialized potato farm ers. Since potato production is readily adaptable to part-time farming, many of these families grew potatoes on a part-time basis or as a minor enterprise, Twenty-four of the 83 farmers interviewed in the Matanuska Valley specialized in potato production with an average of 11 acres per farm. Thirteen of the 18 farmers in the Tanana Valley grew potatoes as a major enterprise averaging 16 acres per farm. Virtually all of the potatoes on the Kenai Peninsula were grown as a minor enterprise or as a part-time venture. As a source of farm income to Alaskan farm ers, potatoes ranked second only to dairy, A major portion of the money spent by potato farmers in both the Matanuska and Tanana Valleys was for improving service buildings and increasing equipment inventories in 1952, The net returns on 24 Matanuska Valley potato farms ranged from a loss of $5, 489 to a net gain of$8, 958 and averaged $3, 446c Three farmers lost money in their farm operations. Yield was the major factor influencing income from potatoes in 1952, Farmers with the higher net return obtained 6,8 tons of U„ S. No, l's per acre as compared with 4,4 tons obtained by farmers realizing less from farming. Both groups had approximately the same acreage of potatoes. Farmers with the higher incomes grossed more and spent less in their business venture than did farmers with lower incomes. Savings were incurred on hired labor, feed, seed, machinery repairs, fuel and oil, and fertilizer. Farmers with the greatest acreage of potatoes netted only$300 more than those with fewer acres. The form er averaged 14 acres of potatoes per farm and the latter 8 acres per farm. Labor costs for farmers with greater acreages were 3 times greater than those for farmers with the lesser acreage. The difference was $1,171, The potato yield per acre on 48 Matanuska Valley farms ranged from 0 to 8,7 tons of U,, Sc No, l ’ s and averaged 5,6 tons. Twenty-eight of these farmers reported above average yields. Local variations occurred among general areas as to both yield and management practices. Average yield was higher in 1 of the 3 general areas and another area used more fertilizer and seed than the third. However, the rates of fertilizer and seed used per acre have been increasing in all areas in recent years. A frost in August severely cut average yield in the Tanana Valley. Some fields were a total loss. In spite of the frost, average net returns on 10 potato farms were$4,019 which was about $600 more than Matanuska Valley potato growers realized. Potato farmers on the Kenai Peninsula were severely handicapped by lack of equipment. Many planted and harvested by hand. Potatoes were a common cash crop; 12 of the 19 farmers interviewed produced small acreaged.In cooperation with the UNITED STATES DEPARTMENT OF AGRICULTUR

Farming in Alaska.

An analysis of commercial farming in Alaska has long been needed. This report may supply helpful information. It spans the yea rs from 1949 to 1954, a time of rapid development and growth. T he study analyzes detailed information supplied by 75 to 85 farmers in the Matanuska Valley and by 15 to 30 others in the Tanana Valley. In 1952, records were also obtained from 19 farmers in the Kenai Peninsula. These record s are estimated to cover about 60 per cent of all commercial farming activity in these particular areas during the period. Information on farming in areas outside the Kenai Peninsula and the Railbelt was gathered from mailed questionnaires supplemented by personal observations. Data for 1949 and 1950 were collected by Clarence A. Moore and were first summarized in his Mimeographed Circular 1, Alaska Farms : Organization and Practices in 1949, and Bulletin 14, Farming in the Matanuska and Tanana Valleys of A laska, both published by the Alaska Agricultural Experiment Station. The authors are grateful to the farmers, agencies and others whose help made this work possible

Rank-based estimation for all-pass time series models

An autoregressive-moving average model in which all roots of the autoregressive polynomial are reciprocals of roots of the moving average polynomial and vice versa is called an all-pass time series model. All-pass models are useful for identifying and modeling noncausal and noninvertible autoregressive-moving average processes. We establish asymptotic normality and consistency for rank-based estimators of all-pass model parameters. The estimators are obtained by minimizing the rank-based residual dispersion function given by Jaeckel [Ann. Math. Statist. 43 (1972) 1449--1458]. These estimators can have the same asymptotic efficiency as maximum likelihood estimators and are robust. The behavior of the estimators for finite samples is studied via simulation and rank estimation is used in the deconvolution of a simulated water gun seismogram.Comment: Published at http://dx.doi.org/10.1214/009053606000001316 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Summary of Ryan’s Express v. Amador Stage Lines, 128 Nev. Adv. Op. 27

The Court considered a motion to disqualify a law firm from participating in the appeal of a failed settlement program

Summary of In re Parental Rights as to S.M.M.D, 128 Nev. Adv. Op. No. 2

The Court considered an appeal from a district court order denying a petition to vacate an earlier certification of relinquishment of parental rights

Health Risks, Past Usage, and Intention to Use Weight Loss Products in Normal Weight Women with High and Low Body Dysphoria

Objective: There are many health risks involved with the use of weight loss products by normal weight women. The mass media may compound this problem through the promotion of weight loss products and a thin body size. This study tested women\u27s perceptions of different weight loss product ads to determine if body dysphoria (i.e., an over concern with body size and shape in normal weight people) was associated with risk beliefs, past behaviors, and intention toward using weight loss products. Method: Normal weight women (age range = 18-41 yr), who were classified as either high (n=45) or low (n=43) on a measure of body dysphoria, rated different weight loss products according to their perception of health risks, past behavior, and their intention to consume the products. These products were a dietary fat substitute (olestra), a prescription obesity medication (sibutramine), and an over-the-counter appetite suppressant (phenylpropanolamine). Results: High body dysphoric women reported higher intentions to use the products as well as increased prior use of two of the three weight loss products. High body dysphoric women did not believe that these weight loss products were harmless. They recognized potential health risks associated with using such products, but nonetheless, expressed intention to use these weight loss products at a higher frequency. Also, several variables related to body image were found to effectively discriminate normal weight women at risk for abusing weight loss products. Discussion: This study found that women who do not need to lose weight but have significant body image concerns were willing to use potentially harmful weight loss products despite the knowledge that such products might pose significant health risks. Techniques utilized by advertising regulatory agencies such as warning labels did not have a strong deterrent effect for stated intentions to use the products. Implications of these findings for public health policy issues were discussed

Earthquake Prediction and Hazards Evaluation in the Year 2000 -- A Dialogue

Decisionmakers have different perspectives about geologic hazards than scientists and engineers. These differences, which have been summarized by Szanton (1981, table 3-1), are the reasons that implementation of loss reduction measures are difficult. The differences are: The ultimate objective of the decisionmaker is the approval of the electorate; it is the respect of peers for the scientist/engineer; The time horizon for the decisionmaker is short; it is long for the scientist/engineer; The focus of the decisionmaker is on the external logic of the problem; it is on the internal logic for the scientist/engineer; The mode of thought for the decisionmaker is deductive and particular; it is inductive and generic for the scientist/engineer; The most valued outcome for the decisionmaker is a reliable solution; it is original insight for the scientist/engineer; The mode of expression is simple and absolute for the decisionmaker; it is abstruse and qualified for the scientist/engineer, and; The preferred form of conclusion for the decisionmaker is one of "best solution" with uncertainties submerged; it is multiple possibilities with uncertainties emphasized for the scientist/engineer. With these principles in mind, let us now turn the clock forward to the year 2000 and a discussion between a decisionmaker and a scientist as they seek to resolve their philosophical differences and reach solutions to problems of earthquake-hazards reduction

Maximum likelihood estimation for α\alpha-stable autoregressive processes

We consider maximum likelihood estimation for both causal and noncausal autoregressive time series processes with non-Gaussian $\alpha$-stable noise. A nondegenerate limiting distribution is given for maximum likelihood estimators of the parameters of the autoregressive model equation and the parameters of the stable noise distribution. The estimators for the autoregressive parameters are $n^{1/\alpha}$-consistent and converge in distribution to the maximizer of a random function. The form of this limiting distribution is intractable, but the shape of the distribution for these estimators can be examined using the bootstrap procedure. The bootstrap is asymptotically valid under general conditions. The estimators for the parameters of the stable noise distribution have the traditional $n^{1/2}$ rate of convergence and are asymptotically normal. The behavior of the estimators for finite samples is studied via simulation, and we use maximum likelihood estimation to fit a noncausal autoregressive model to the natural logarithms of volumes of Wal-Mart stock traded daily on the New York Stock Exchange.Comment: Published in at http://dx.doi.org/10.1214/08-AOS632 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org