The technical efficiency of large-scale agricultural investment in Northwest Ethiopia: A stochastic frontier approach. [PDF]
Heliyon, 2023 Motbaynor Workneh W, Kumar R.
europepmc +1 more source
Confidence Statements for Efficiency Estimates from Stochastic Frontier Models [PDF]
This paper is an empirical study of the uncertainty associated with estimates from stochastic frontier models. We show how to construct confidence intervals for estimates of technical efficiency levels under different sets of assumptions ranging from the
Peter Schmidt, William C. Horrace
core
The Multifractal Nature of Volterra-L\'{e}vy Processes [PDF]
, 2014 We consider the regularity of sample paths of Volterra-L\'{e}vy processes. These processes are defined as stochastic integrals $$ M(t)=\int_{0}^{t}F(t,r)dX(r), \ \ t \in \mathds{R}_{+}, $$ where $X$ is a L\'{e}vy process and $F$ is a deterministic real ...
Neuman, Eyal
core +1 more source
Agribusiness, EarlyView.ABSTRACT This study sets out to investigate the prospects for raising oil palm output in sub‐Saharan Africa, particularly Ghana, without further expansion of cropland. Given global concerns about oil palm's role in deforestation and land use change, the focus is on enhancing productivity on existing farmlands.
Jacob Asravor +3 more
wiley +1 more source
On estimating the effectiveness of resources. A local maximum likelihood frontier approach on care for students [PDF]
To study education as a complex production process in a noisy and heterogeneous setting, this paper suggests to using a stochastic frontier model estimated by a local maximum likelihood approach (LMLSF). The LMLSF smoothly combines the virtues of the non-
De Witte, K., Verschelde, M.
core
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Stochastic frontier approach to efficiency analysis of health facilities in providing services for non-communicable diseases in eight LMICs. [PDF]
Int Health, 2023 Bala MM, Singh S, Gautam DK.
europepmc +1 more source
Estimation of semiparametric stochastic frontiers under shape constraints with application to pollution generating technologies [PDF]
A number of studies have explored the semi- and nonparametric estimation of stochastic frontier models by using kernel regression or other nonparametric smoothing techniques. In contrast to popular deterministic nonparametric estimators, these approaches
Kortelainen, Mika
core +1 more source
Stochastic frontier models: a bayesian perspective [PDF]
, 1992 A Bayesian approach to estimation, prediction and model comparison in composed error production models is presented. A broad range of distributions on the inefficiency term define the contending models, which can either be treated separately or pooled ...
Broeck, Julien Van den +3 more
core +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
Advanced Intelligent Discovery, EarlyView.The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source