Faculty Research Publications (Statistics)http://hdl.handle.net/1957/296562015-11-26T08:58:57Z2015-11-26T08:58:57ZSubsampling Bootstrap of Count Features of NetworksBhattacharyya, SharmodeepBickel, Peter J.http://hdl.handle.net/1957/577852015-11-19T17:58:08Z2015-12-01T00:00:00ZSubsampling Bootstrap of Count Features of Networks
Bhattacharyya, Sharmodeep; Bickel, Peter J.
Analysis of stochastic models of networks is quite important in light of
the huge influx of network data in social, information and bio sciences, but
a proper statistical analysis of features of different stochastic models of networks
is still underway.We propose bootstrap subsampling methods for finding
empirical distribution of count features or “moments” (Bickel, Chen and
Levina [Ann. Statist. 39 (2011) 2280–2301]) and smooth functions of these
features for the networks. Using these methods, we cannot only estimate the
variance of count features but also get good estimates of such feature counts,
which are usually expensive to compute numerically in large networks. In our
paper, we prove theoretical properties of the bootstrap estimates of variance
of the count features as well as show their efficacy through simulation. We
also use the method on some real network data for estimation of variance and
expectation of some count features.
This is the publisher’s final pdf. The published article is copyrighted by Institute of Mathematical Statistics and can be found at: http://projecteuclid.org/euclid.aos/1444222079
2015-12-01T00:00:00ZIrrigation and Fertigation with Drip and Alternative Micro Irrigation Systems in Northern Highbush BlueberryVargas, Oscar L.Bryla, David R.Weiland, Jerry E.Strik, Bernadine C.Sun, Lunahttp://hdl.handle.net/1957/569422015-08-27T14:32:53Z2015-06-01T00:00:00ZIrrigation and Fertigation with Drip and Alternative Micro Irrigation Systems in Northern Highbush Blueberry
Vargas, Oscar L.; Bryla, David R.; Weiland, Jerry E.; Strik, Bernadine C.; Sun, Luna
The use of conventional drip and alternative micro irrigation systems were
evaluated for 3 years in six newly planted cultivars (Earliblue, Duke, Draper, Bluecrop,
Elliott, and Aurora) of northern highbush blueberry (Vaccinium corymbosum L.). The
drip system included two lines of tubing on each side of the row with in-line drip emitters
at every 0.45 m. The alternative systems included geotextile tape and microsprinklers.
The geotextile tape was placed alongside the plants and dispersed water and nutrients
over the entire length. Microsprinklers were installed between every other plant at
a height of 1.2 m. Nitrogen was applied by fertigation at annual rates of 100 and
200 kg·ha⁻¹ N by drip, 200 kg·ha⁻¹1 N by geotextile tape, and 280 kg·ha⁻¹ N by microsprinklers.
By the end of the first season, plant size, in terms of canopy cover, was greatest
with geotextile tape, on average, and lowest with microsprinklers or drip at the lower N
rate. The following year, canopy cover was similar with geotextile tape and drip at the
higher N rate in each cultivar, and was lowest with microsprinklers in all but ‘Draper’. In
most of the cultivars, geotextile tape and drip at the higher N rate resulted in greater leaf
N concentrations than microsprinklers or drip at the lower N rate, particularly during
the first year after planting. By the third year, yield averaged 3.1–9.1 t·ha⁻¹ among the
cultivars, but was similar with geotextile tape and drip at either N rate, and was only
lower with microsprinklers. Overall, drip was more cost effective than geotextile tape,
and fertigation with 100 kg·ha⁻¹ N by drip was sufficient to maximize early fruit
production in each cultivar. Microsprinklers were less effective by comparison and
resulted in white salt deposits on the fruit
To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by American Society for Horticultural Science and can be found at: http://hortsci.ashspublications.org/
2015-06-01T00:00:00ZDesigning a Monitoring Program to Estimate Estuarine Survival of Anadromous Salmon Smolts: Simulating the Effect of Sample Design on InferenceRomer, Jeremy D.Gitelman, Alix I.Clements, ShaunSchreck, Carl B.http://hdl.handle.net/1957/568332015-08-21T18:52:30Z2015-07-21T00:00:00ZDesigning a Monitoring Program to Estimate Estuarine Survival of Anadromous Salmon Smolts: Simulating the Effect of Sample Design on Inference
Romer, Jeremy D.; Gitelman, Alix I.; Clements, Shaun; Schreck, Carl B.
A number of researchers have attempted to estimate salmonid smolt survival during outmigration through an estuary. However, it is currently unclear how the design of such studies influences the accuracy and precision of survival estimates. In this simulation study we consider four patterns of smolt survival probability in the estuary, and test the performance of several different sampling strategies for estimating estuarine survival assuming perfect detection. The four survival probability patterns each incorporate a systematic component (constant, linearly increasing, increasing and then decreasing, and two pulses) and a random component to reflect daily fluctuations in survival probability. Generally, spreading sampling effort (tagging) across the season resulted in more accurate estimates of survival. All sampling designs in this simulation tended to under-estimate the variation in the survival estimates because seasonal and daily variation in survival probability are not incorporated in the estimation procedure. This under-estimation results in poorer performance of estimates from larger samples. Thus, tagging more fish may not result in better estimates of survival if important components of variation are not accounted for. The results of our simulation incorporate survival probabilities and run distribution data from previous studies to help illustrate the tradeoffs among sampling strategies in terms of the number of tags needed and distribution of tagging effort. This information will assist researchers in developing improved monitoring programs and encourage discussion regarding issues that should be addressed prior to implementation of any telemetry-based monitoring plan. We believe implementation of an effective estuary survival monitoring program will strengthen the robustness of life cycle models used in recovery plans by providing missing data on where and how much mortality occurs in the riverine and estuarine portions of smolt migration. These data could result in better informed management decisions and assist in guidance for more effective estuarine restoration projects.
To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The article was published by the Public Library of Science and is in the public domain. The published article can be found at: http://www.plosone.org/.
2015-07-21T00:00:00ZEstimating wind-turbine-caused bird and bat fatality when zero carcasses are observedHuso, Manuela M. P.Dalthorp, DanDail, DavidMadsen, Lisahttp://hdl.handle.net/1957/566722015-08-13T17:35:45Z2015-07-01T00:00:00ZEstimating wind-turbine-caused bird and bat fatality when zero carcasses are observed
Huso, Manuela M. P.; Dalthorp, Dan; Dail, David; Madsen, Lisa
Many wind-power facilities in the United States have established effective monitoring programs to determine turbine-caused fatality rates of birds and bats, but estimating the number of fatalities of rare species poses special difficulties. The loss of even small numbers of individuals may adversely affect fragile populations, but typically, few (if any) carcasses are observed during monitoring. If monitoring design results in only a small proportion of carcasses detected, then finding zero carcasses may give little assurance that the number of actual fatalities is small. Fatality monitoring at wind-power facilities commonly involves conducting experiments to estimate the probability (g) an individual will be observed, accounting for the possibilities that it falls in an unsearched area, is scavenged prior to detection, or remains undetected even when present. When g < 1, the total carcass count (X) underestimates the total number of fatalities (M). Total counts can be 0 when M is small or when M is large and g ≪1. Distinguishing these two cases is critical when estimating fatality of a rare species. Observing no individuals during searches may erroneously be interpreted as evidence of absence. We present an approach that uses Bayes' theorem to construct a posterior distribution for M, i.e., P(M\ X, ĝ), reflecting the observed carcass count and previously estimated g. From this distribution, we calculate two values important to conservation: the probability that M is below a predetermined limit and the upper bound (M*) of the 100(1 − α)% credible interval for M. We investigate the dependence of M* on α, g, and the prior distribution of M, asking what value of g is required to attain a desired M* for a given α. We found that when g < ~0.15, M* was clearly influenced by the mean and variance of ĝ and the choice of prior distribution for M, but the influence of these factors is minimal when g > ~0.45. Further, we develop extensions for temporal replication that can inform prior distributions of M and methods for combining information across several areas or time periods. We apply the method to data collected at a wind-power facility where scheduled searches yielded X = 0 raptor carcasses.
To the best of our knowledge, one or more authors of this paper were federal employees when contributing to this work. This is the publisher’s final pdf. The published article is copyrighted by Ecological Society of America and can be found at: http://www.esajournals.org/loi/ecap; Appendices A and B and the Supplement are available online: http://dx.doi.org/10.1890/14-0764.1.sm
2015-07-01T00:00:00Z