Search results for "Modelling"
showing 10 items of 1353 documents
A dynamic business modelling approach to design and experiment new business venture strategies
2018
Abstract Business Modelling has evolved as a key activity to reflect new business venture strategy by framing the way a firm will operate and how it will function in achieving its goals (e.g., profitability, growth, innovation, social impact). However, scholars and practitioners have criticized the adoption of a too static perspective in the design and use of conventional Business Model representations. Such a static perspective prevents nascent entrepreneurs experimenting with their Business Models and, as a result, identifying the most effective strategies, especially in terms of business sustainability and profitability. In this paper, we argue that combining conventional Business Model …
Importance of the Window Function Choice for the Predictive Modelling of Memristors
2021
Window functions are widely employed in memristor models to restrict the changes of the internal state variables to specified intervals. Here, we show that the actual choice of window function is of significant importance for the predictive modelling of memristors. Using a recently formulated theory of memristor attractors, we demonstrate that whether stable fixed points exist depends on the type of window function used in the model. Our main findings are formulated in terms of two memristor attractor theorems, which apply to broad classes of memristor models. As an example of our findings, we predict the existence of stable fixed points in Biolek window function memristors and their absenc…
A penalized approach to covariate selection through quantile regression coefficient models
2019
The coefficients of a quantile regression model are one-to-one functions of the order of the quantile. In standard quantile regression (QR), different quantiles are estimated one at a time. Another possibility is to model the coefficient functions parametrically, an approach that is referred to as quantile regression coefficients modeling (QRCM). Compared with standard QR, the QRCM approach facilitates estimation, inference and interpretation of the results, and generates more efficient estimators. We designed a penalized method that can address the selection of covariates in this particular modelling framework. Unlike standard penalized quantile regression estimators, in which model selec…
Weather Derivatives and Stochastic Modelling of Temperature
2011
We propose a continuous-time autoregressive model for the temperature dynamics with volatility being the product of a seasonal function and a stochastic process. We use the Barndorff-Nielsen and Shephard model for the stochastic volatility. The proposed temperature dynamics is flexible enough to model temperature data accurately, and at the same time being analytically tractable. Futures prices for commonly traded contracts at the Chicago Mercantile Exchange on indices like cooling- and heating-degree days and cumulative average temperatures are computed, as well as option prices on them.
Expert-based versus citation-based ranking of scholarly and scientific publication channels
2016
Abstract The Finnish publication channel quality ranking system was established in 2010. The system is expert-based, where separate panels decide and update the rankings of a set of publications channels allocated to them. The aggregated rankings have a notable role in the allocation of public resources into universities. The purpose of this article is to analyze this national ranking system. The analysis is mainly based on two publicly available databases containing the publication source information and the actual national publication activity information. Using citation-based indicators and other available information with association rule mining, decision trees, and confusion matrices, …
Covid-19 in Italy: Modelling, Communications, and Collaborations
2022
Abstract When Covid-19 arrived in Italy in early 2020, a group of statisticians came together to provide tools to make sense of the unfolding epidemic and to counter misleading media narratives. Here, members of StatGroup-19 reflect on their work to date
Parametric estimation of non-crossing quantile functions
2021
Quantile regression (QR) has gained popularity during the last decades, and is now considered a standard method by applied statisticians and practitioners in various fields. In this work, we applied QR to investigate climate change by analysing historical temperatures in the Arctic Circle. This approach proved very flexible and allowed to investigate the tails of the distribution, that correspond to extreme events. The presence of quantile crossing, however, prevented using the fitted model for prediction and extrapolation. In search of a possible solution, we first considered a different version of QR, in which the QR coefficients were described by parametric functions. This alleviated th…
Quantitative Analysis of Experimental and Synthetic Microstructures for Sedimentary Rock
1999
A quantitative comparison between the experimental microstructure of a sedimentary rock and three theoretical models for the same rock is presented. The microstructure of the rock sample (Fontainebleau sandstone) was obtained by microtomography. Two of the models are stochastic models based on correlation function reconstruction, and one model is based on sedimentation, compaction and diagenesis combined with input from petrographic analysis. The porosity of all models closely match that of the experimental sample and two models have also the same two point correlation function as the experimental sample. We compute quantitative differences and similarities between the various microstructur…
A spatially filtered mixture of β-convergence regressions for EU regions, 1980–2002
2007
Assessing regional growth and convergence across Europe is a matter of primary relevance. Empirical models that do not account for structural heterogeneities and spatial effects may face serious misspecification problems. In this work, a mixture regression approach is applied to the beta-convergence model, in order to produce an endogenous selection of regional growth patterns. A priori choices, such as North-South or centre-periphery divisions, are avoided. In addition to this, we deal with the spatial dependence existing in the data, applying a local filter to the data. The results indicate that spatial effects matter, and either absolute, conditional, or club convergence, if extended to …
Large deviations results for subexponential tails, with applications to insurance risk
1996
AbstractConsider a random walk or Lévy process {St} and let τ(u) = inf {t⩾0 : St > u}, P(u)(·) = P(· | τ(u) < ∞). Assuming that the upwards jumps are heavy-tailed, say subexponential (e.g. Pareto, Weibull or lognormal), the asymptotic form of the P(u)-distribution of the process {St} up to time τ(u) is described as u → ∞. Essentially, the results confirm the folklore that level crossing occurs as result of one big jump. Particular sharp conclusions are obtained for downwards skip-free processes like the classical compound Poisson insurance risk process where the formulation is in terms of total variation convergence. The ideas of the proof involve excursions and path decompositions for Mark…