22 research outputs found
systemfit: A Package for Estimating Systems of Simultaneous Equations in R
Many statistical analyses (e.g., in econometrics, biostatistics and experimental design) are based on models containing systems of structurally related equations. The systemfit package provides the capability to estimate systems of linear equations within the R programming environment. For instance, this package can be used for "ordinary least squares" (OLS), "seemingly unrelated regression" (SUR), and the instrumental variable (IV) methods "two-stage least squares" (2SLS) and "three-stage least squares" (3SLS), where SUR and 3SLS estimations can optionally be iterated. Furthermore, the systemfit package provides tools for several statistical tests. It has been tested on a variety of datasets and its reliability is demonstrated.
systemfit: A Package for Estimating Systems of Simultaneous Equations in R
Many statistical analyses (e.g., in econometrics, biostatistics and experimental design) are based on models containing systems of structurally related equations. The systemfit package provides the capability to estimate systems of linear equations within the R programming environment. For instance, this package can be used for "ordinary least squares" (OLS), "seemingly unrelated regression" (SUR), and the instrumental variable (IV) methods "two-stage least squares" (2SLS) and "three-stage least squares" (3SLS), where SUR and 3SLS estimations can optionally be iterated. Furthermore, the systemfit package provides tools for several statistical tests. It has been tested on a variety of datasets and its reliability is demonstrated
Recommended from our members
Optimizing the primary forest products supply chain : a multi-objective heuristic approach
This thesis is a collection of four submitted manuscripts that present
methods to assist forest ecosystem service managers wanting to develop
operational sampling, monitoring, and production plans for a set of
specific quantifiable ecosystem services, which are formulated as a
series of general multi-objective optimization problems. The problems
are solved using a heuristic solution technique to determine the best
trade-off, efficient, or Pareto frontiers, among the potentially
competing and possibly non-commensurate objectives, with the intention
that the decision maker(s) will select and implement a single plan
from the Pareto frontier.
The first manuscript presents the general formulation and solution
framework, and demonstrates the method with a problem that has five
objectives. The method demonstrates that Pareto frontiers for problems
with unknown inputs, many competing objectives, and complex
constraints can be analyzed using simple search rules.
The second manuscript examines design-based estimation and model-based
prediction methods to obtain guesses of unknown inputs, and the
resulting outputs, for operational production plans. The results
indicate that model-based prediction methods, using simple correlation
models, provide benefits by reducing production uncertainties, and
thus offer substantial cost savings, or increases in net revenue, when
comparison to traditional design-based methods.
The third manuscript approximates the Pareto frontier between the
maximum information content (i.e. entropy) and the minumum cost for a
forest sample, where the results from the sample will be used for many
objectives (e.g. prediction, simulation, and optimization). The
results depend on the definition of the sample design, but follow
similar patterns for all 36 sample designs examined.
Finally, the fourth manuscript presents an examination of the Pareto
frontier for an operational harvest schedule, using the sample that
contains the maximum information content, and the objectives for the
operation must satisfy multiple internal and external customers (i.e.
production, financial, environmental, logistics, and marketing).
By including additional information (i.e. spatial correlation) in the
prediction, simulation, and optimization process, these manuscripts
demonstrate substantial potential increases in financial objectives
(i.e. maximize net revenue, minimize costs), environmental objectives
(i.e. maximize unharvested area), materials management objectives
(i.e. minimize product degredation), information objectives (i.e.
maximum entopy sampling) as well as provide a framework for the
objective examination of complex forest ecosystem supply chain
problems with multiple objectives
Recommended from our members
Simultaneous equation estimation for individual tree growth in young Southern Oregon and Northern California conifer plantations
This thesis presents methods for obtaining asymptotically efficient and consistent parameters and variance estimates for simultaneous equations in a forest growth modelling context. Ordinary Least Squares (OLS), Seemingly Unrelated Regressions (SUR), Two-Stage Least Squares (2SLS) and Three- Stage Least Squares (3SLS) are presented for linear models. The variables, model types and transformations are examined for appropriateness in diameter and height growth models in young stands. A basal diameter growth, height growth and static crown ratio model were developed using the methods described. Model performance was measured by the ratio of the standard-errors of the predictions for basal diameter growth, height growth and crown ratio as described by Hasenauer et al. (1998). The 3SLS model performed better than the 2SLS or OLS for the basal diameter growth. The advantages of using 3SLS over 2SLS or OLS for the height growth and crown ratio models were minimal. Finally, a simultaneous equation estimation package was developed for the R (Ihaka and Gentleman, 1996) open-source computer program
Selection and Penalty Strategies for Genetic Algorithms Designed to Solve Spatial Forest Planning Problems
Genetic algorithms (GAs) have demonstrated success in solving spatial forest planning problems. We present an adaptive GA that incorporates population-level statistics to dynamically update penalty functions, a process analogous to strategic oscillation from the tabu search literature. We also explore performance of various selection strategies. The GA identified feasible solutions within 96%, 98%, and 93% of a nonspatial relaxed upper bound calculated for landscapes of 100, 500, and 1000 units, respectively. The problem solved includes forest structure constraints limiting harvest opening sizes and requiring minimally sized patches of mature forest. Results suggest that the dynamic penalty strategy is superior to the more standard static penalty implementation. Results also suggest that tournament selection can be superior to the more standard implementation of proportional selection for smaller problems, but becomes susceptible to premature convergence as problem size increases. It is therefore important to balance selection pressure with appropriate disruption. We conclude that integrating intelligent search strategies into the context of genetic algorithms can yield improvements and should be investigated for future use in spatial planning with ecological goals
OxideâBased SolidâState Batteries: A Perspective on Composite Cathode Architecture
The garnet-type phase LiLaZrO (LLZO) attracts significant attention as an oxide solid electrolyte to enable safe and robust solid-state batteries (SSBs) with potentially high energy density. However, while significant progress has been made in demonstrating compatibility with Li metal, integrating LLZO into composite cathodes remains a challenge. The current perspective focuses on the critical issues that need to be addressed to achieve the ultimate goal of an all-solid-state LLZO-based battery that delivers safety, durability, and pack-level performance characteristics that are unobtainable with state-of-the-art Li-ion batteries. This perspective complements existing reviews of solid/solid interfaces with more emphasis on understanding numerous homo- and heteroionic interfaces in a pure oxide-based SSB and the various phenomena that accompany the evolution of the chemical, electrochemical, structural, morphological, and mechanical properties of those interfaces during processing and operation. Finally, the insights gained from a comprehensive literature survey of LLZOâcathode interfaces are used to guide efforts for the development of LLZO-based SSBs
A combined analysis of outcome following breast cancer: differences in survival based on BRCA1/BRCA2 mutation status and administration of adjuvant treatment
BACKGROUND: The prognostic significance of germline mutations in BRCA1 and BRCA2 in women with breast cancer remains unclear. A combined analysis was performed to address this uncertainty. METHODS: Two retrospective cohorts of Ashkenazi Jewish women undergoing breast-conserving treatment for invasive cancer between 1980 and 1995 (n = 584) were established. Archived tissue blocks were used as the source of DNA for Ashkenazi Jewish BRCA1/BRCA2 founder mutation analysis. Paraffin-embedded tissue and follow-up information was available for 505 women. RESULTS: Genotyping was successful in 496 women, of whom 56 (11.3%) were found to carry a BRCA1/BRCA2 founder mutation. After a median follow-up period of 116 months, breast cancer specific survival was worse in women with BRCA1 mutations than in those without (62% at 10 years versus 86%; P < 0.0001), but not in women with the BRCA2 mutation (84% versus 86% at 10 years; P = 0.76). Germline BRCA1 mutations were an independent predictor of breast cancer mortality in multivariate analysis (hazard ratio 2.4, 95% confidence interval 1.2â4.8; P = 0.01). BRCA1 status predicted breast cancer mortality only among women who did not receive chemotherapy (hazard ratio 4.8, 95% confidence interval 2.0â11.7; P = 0.001). The risk for metachronous ipsilateral cancer was not greater in women with germline BRCA1/BRCA2 founder mutations than in those without mutations (P = 0.68). CONCLUSION: BRCA1 mutations, but not BRCA2 mutations, are associated with reduced survival in Ashkenazi women undergoing breast-conserving treatment for invasive breast cancer, but the poor prognosis associated with germline BRCA1 mutations is mitigated by adjuvant chemotherapy. The risk for metachronous ipsilateral disease does not appear to be increased for either BRCA1 or BRCA2 mutation carriers, at least up to 10 years of follow up