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  • 201. Wang, Yu
    et al.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Är kommunala sommarjobb en gräddfil till arbetsmarknaden?2006Report (Other academic)
  • 202. Wei, Yixuan
    et al.
    Xia, Liang
    Pan, Song
    Wu, Jinshun
    Zhang, Xingxing
    Dalarna University, School of Technology and Business Studies, Energy Technology.
    Han, Mengjie
    Dalarna University, School of Technology and Business Studies, Statistics.
    Zhang, Weiya
    Xie, Jingchao
    Li, Qingping
    Prediction of occupancy level and energy consumption in office building using blind system identification and neural networks2019In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 240, p. 276-294Article in journal (Refereed)
    Abstract [en]

    Occupancy behaviour plays an important role in energy consumption in buildings. Currently, the shallow understanding of occupancy has led to a considerable performance gap between predicted and measured energy use. This paper presents an approach to estimate the occupancy based on blind system identification (BSI), and a prediction model of electricity consumption by an air-conditioning system is developed and reported based on an artificial neural network with the BSI estimation of the number of occupants as an input. This starts from the identification of indoor CO2 dynamics derived from the mass-conservation law and venting levels. The unknown parameters, including the occupancy and model parameters, are estimated by using a frequentist maximum-likelihood algorithm and Bayesian estimation. The second phase is to establish the prediction model of the electricity consumption of the air-conditioning system by using a feed-forward neural network (FFNN) and extreme learning machine (ELM), as well as ensemble models. To analyse some aspects of the benchmark test for identifying the effect of structure parameters and input-selection alternatives, three studies are conducted on (1) the effect of predictor selection based on principal component analysis, (2) the effect of the estimated occupancy as the supplementary input, and (3) the effect of the neural network ensemble. The result shows that the occupancy number, as the input, is able to improve the accuracy in predicting energy consumption using a neural network model.

  • 203.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A finite sample improvement of the fixed effects estimator applied to technical inefficiency2015In: Journal of Productivity Analysis, ISSN 0895-562X, E-ISSN 1573-0441, Vol. 43, no 1, p. 29-46Article in journal (Refereed)
    Abstract [en]

    The fixed effects (‘FE’) estimator of technical inefficiency performs poorly when N (the ’number of firms’) is large and T (the ‘number of time observations’) is small. We propose kernel estimators, which includes the FE estimator as a special case. In terms of criteria based on collective conditional ‘mean square error’, it is demonstrated that some kernel estimators are more efficient than the FE estimators of firm effects and inefficiencies in finite sample settings. Monte Carlo simulations support our theoretical findings, and we use an empirical example to show how FE estimation and kernel estimation lead to very different conclusions about technical inefficiency among Indonesian rice farmers.

  • 204.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A finite sample improvement of the fixed effects estimator: applied to technical infficiency2013Report (Other academic)
    Abstract [en]

    The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.

  • 205.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    A Note on Proxy Variables and Instrument Variable Regression2015Report (Other academic)
    Abstract [en]

    This is a note about proxy variables and instruments for identification of structural parameters in regression models. We have experienced that in the econometric textbooks these two issues are treated separately, although in practice these two concepts are very often combined. Usually, proxy variables are inserted in instrument variable regressions with the motivation they are exogenous. Implicitly meaning they are exogenous in a reduced form model and not in a structural model. Actually if these variables are exogenous they should be redundant in the structural model, e.g. IQ as a proxy for ability. Valid proxies reduce unexplained variation and increases the efficiency of the estimator of the structural parameter of interest. This is especially important in situations when the instrument is weak. With a simple example we demonstrate what is required of a proxy and an instrument when they are combined. It turns out that when a researcher has a valid instrument the requirements on the proxy variable is weaker than if no such instrument exists

  • 206.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Consistent method of moments estimation of the true fixed effects model2015Report (Other academic)
  • 207.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Consistent method of moments estimation of the true fixed effects model2015In: Economics Letters, ISSN 0165-1765, E-ISSN 1873-7374, Vol. 137, p. 62-69Article in journal (Refereed)
    Abstract [en]

    About a decade ago William H. Greene introduced the so-called ‘True fixed effects’ (TFE) model, which is intended to discriminate between heterogeneity and efficiency in stochastic frontier analysis. We would say that the TFE model has had a huge impact on applied stochastic frontier analysis. One problem with the original TFE estimator, is its inconsistency in cases with finite time observations, at least for the variance components. For the normal-half-normal model, this problem was solved by Chen et al. (2014) based on maximum likelihood estimation of the within-transformed model. In this study, we illustrate the possibilities offered by method of moments estimation. This approach is more flexible than the MLE proposed by Chen et al. (2014), since the method of moments estimators are not so closely dependent on the distributional assumptions and do not hinge on an explicit distribution of the random error. We only assume symmetry, as well as a fixed fourth-order cumulant for more complicated models. Greene’s methodology can, and has been, generalized to other models than the normal-half-normal model. However, the method of moments estimators proposed here are consistent.

  • 208.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Modified fixed effects estimation of technical inefficiency2016In: Journal of Productivity Analysis, ISSN 0895-562X, E-ISSN 1573-0441, Vol. 46, no 1, p. 83-86Article in journal (Refereed)
    Abstract [en]

    We consider method-of-moments fixed effects (FE) estimation of technical inefficiency. When dealing with a large number of cross-sectional observations, N, it is possible to obtain consistent moment estimators of the inefficiency distribution. It is well known that the classical FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. The method-of-moments FE estimators do not suffer from this type of bias in large-N settings. The proposed methodology bridges classical FE and maximum likelihood estimation, leading to a reduction in bias without making the random effects assumption.

  • 209.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics. Swedish University of Agricultural Sciencies.
    Modified Fixed Effects Estimation of Technical Inefficiency2013Report (Other academic)
    Abstract [en]

    We consider method of moment fixed effects (FE) estimation of technical inefficiency. When N, the number of cross sectional observations, is large it ispossible to obtain consistent central moments of the population distribution of the inefficiencies. It is well-known that the traditional FE estimator may be seriously upward biased when N is large and T, the number of time observations, is small. Based on the second central moment and a single parameter distributional assumption on the inefficiencies, we obtain unbiased technical inefficiencies in large N settings. The proposed methodology bridges traditional FE and maximum likelihood estimation – bias is reduced without the random effects assumption.

  • 210.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    Slutrapport om kväveoxidavgiftens effekt på kväveoxidutsläppen2015Report (Other academic)
  • 211.
    Wikström, Daniel
    Dalarna University, School of Technology and Business Studies, Statistics.
    The true fixed effects model with non-stationary inefficiency distribution2015Report (Other academic)
  • 212.
    Wikström, Daniel
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Brandt, Daniel
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Heldt, Tobias
    Dalarna University, School of Technology and Business Studies, Economics.
    A business intelligence solution of handling traveling data with R and Shiny2016In: Proceedings of the IFITTtalk@Östersund Workshop on Big Data & Business Intelligence in the Travel & Tourism Domain / [ed] Fuchs, M., Lexhagen, M. & Höpken, W., 2016Conference paper (Refereed)
  • 213.
    Xiao, Yumin
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Wang, Heng
    Dalarna University, School of Technology and Business Studies, Statistics.
    Aviation accident insurance: actuarial modeling, pricing, and demonstrating the long-term risk via simulation2010Independent thesis Basic level (degree of Bachelor)Student thesis
    Abstract [en]

    Background: Since the 9.11 air disaster has happened, the degree of concern for aviation accident insurance is higher than before. Having been reformed for several times since 1989, the aviation accident insurance is still dissatisfied with the reality in China. The view that the aviation accident insurance can make huge profits spreads widely. Two obvious defects, huge profits and lack of risk resisting abilities, needs to be solved by the insurers. To understand the problem and propose reasonable strategies, we introduced an actuarial model and did simulations for different scenarios, to see how the premium and risk are connected on the long-term scale. Results: Our simulation results show a monotonic pattern between the yearly premium and the bankruptcy probability for scenarios of 50-200 years periods. Only for the low accident rate of 1/8000000 which is close to the Chinese situation, a yearly premium amount of a single-crash compensation can control the bankruptcy probability to about 5%. Conclusions: The accident rate of the insured airlines needs to be controlled to reduce risk, comprehensive reserve system and reinsurance might also need to be set up.

  • 214.
    Youngjo, Lee
    et al.
    Seoul National University.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, Maengseok
    Pukyong National University, Korea.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Skarin, Anna
    Swedish University of Agricultural Science, Uppsala.
    Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts2016In: Ecology and Evolution, ISSN 2045-7758, E-ISSN 2045-7758, Vol. 6, no 19, p. 7047-7056Article in journal (Refereed)
    Abstract [en]

    We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.

  • 215. Zan, Yanjun
    et al.
    Sheng, Zheya
    Lillie, Mette
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics. SLU.
    Honaker, Christa F
    Siegel, Paul B
    Carlborg, Örjan
    Artificial selection response due to polygenic adaptation from a multilocus, multiallelic genetic architecture2017In: Molecular biology and evolution, ISSN 0737-4038, E-ISSN 1537-1719, Vol. 34, no 10, p. 2678-2689Article in journal (Refereed)
    Abstract [en]

    The ability of a population to adapt to changes in their living conditions, whether in nature or captivity, often depends on polymorphisms in multiple genes across the genome. In-depth studies of such polygenic adaptations are difficult in natural populations, but can be approached using the resources provided by artificial selection experiments. Here, we dissect the genetic mechanisms involved in long-term selection responses of the Virginia chicken lines, populations that after 40 generations of divergent selection for 56-day body weight display a 9-fold difference in the selected trait. In the F15 generation of an intercross between the divergent lines, 20 loci explained >60% of the additive genetic variance for the selected trait. We focused particularly on fine-mapping seven major QTL that replicated in this population and found that only two fine-mapped to single, bi-allelic loci; the other five contained linked loci, multiple alleles or were epistatic. This detailed dissection of the polygenic adaptations in the Virginia lines provides a deeper understanding of the range of different genome-wide mechanisms that have been involved in these long-term selection responses. The results illustrate that the genetic architecture of a highly polygenic trait can involve a broad range of genetic mechanisms, and that this can be the case even in a small population bred from founders with limited genetic diversity.

  • 216.
    Zhang, Liming
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Han, Yang
    Dalarna University, School of Technology and Business Studies, Statistics.
    Detecting Major Genes Controlling Robustness of Chicken Body Weight Using Double Generalized Linear Models2010Independent thesis Advanced level (degree of Master (Two Years))Student thesis
    Abstract [en]

    Detecting both the majors genes that control the phenotypic mean and those controlling phenotypic variance has been raised in quantitative trait loci analysis. In order to mapping both kinds of genes, we applied the idea of the classic Haley-Knott regression to double generalized linear models. We performed both kinds of quantitative trait loci detection for a Red Jungle Fowl x White Leghorn F2 intercross using double generalized linear models. It is shown that double generalized linear model is a proper and efficient approach for localizing variance-controlling genes. We compared two models with or without fixed sex effect and prefer including the sex effect in order to reduce the residual variances. We found that different genes might take effect on the body weight at different time as the chicken grows.

  • 217.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of car-movements in Borlänge, Sweden2014Report (Other academic)
    Abstract [en]

    The advancement of GPS technology enables GPS devices not only to be used as orientation and navigation tools, but also to track travelled routes. GPS tracking data provides essential information for a broad range of urban planning applications such as transportation routing and planning, traffic management and environmental control. This paper describes on processing the data that was collected by tracking the cars of 316 volunteers over a seven-week period. The detailed information is extracted. The processed data is further connected to the underlying road network by means of maps. Geographical maps are applied to check how the car-movements match the road network. The maps capture the complexity of the car-movements in the urban area. The results show that 90% of the trips on the plane match the road network within a tolerance.

  • 218.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of spatiotemporal car movements: a case study2015Report (Other academic)
    Abstract [en]

    The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatiotemporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step-by-step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden.

  • 219.
    Zhao, Xiaoyun
    Dalarna University, School of Technology and Business Studies, Statistics.
    On processing GPS tracking data of spatio-temporal car movements: a case study2015In: Journal of Location Based Services, ISSN 1748-9725, Vol. 9, no 4, p. 235-253Article in journal (Refereed)
    Abstract [en]

    The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatio-temporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step by step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden. 

  • 220.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Dan, Zhiguang
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Network density and the p-median solution2013Report (Other academic)
    Abstract [en]

    The p-medianmodel is commonly used to find optimal locations of facilities for geographically distributed demands. So far, there are few studies that have considered the importance of the road network in the model. However, Han, Håkansson, and Rebreyend (2013) examined the solutions of the p-median model with densities of the road network varying from 500 to 70,000 nodes. They found as the density went beyond some 10,000 nodes, solutions have no further improvements but gradually worsen. The aim of this study is to check their findings by using an alternative heuristic being vertex substitution, as a complement to their using simulated annealing. We reject the findings in Han et al (2013). The solutions do not further improve as the nodes exceed 10,000, but neither do the solutions deteriorate.

  • 221.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    An Evaluation of the Reliability of GPS-Based Transportation Data2014Report (Other academic)
    Abstract [en]

    GPS-based data are becoming a cornerstone for real-time transportation applications. Tracking data of vehicles from GPS receivers are however susceptible to measurement errors. The assessment of the reliability of data from GPS receiver is a neglected issue, especially in a real road network setting and in the phase after data transfer but before information identification. An evaluation method is outlined and carried out by conducting a randomized experiment. We assess the reliability of GPS-based transportation data on geographical position, speed, and elevation from three varied receivers GlobalSat BT-338X, Magellan SporTrak Pro and smart phone for three transportation modes: bicycle, car, and bus. The positional error ranging from 0158 meters, and 74% to 100% with an error within 5 meters depending on the transportation mode and route, there is also a non-negligible risk for aberrant positioning. Speed is slightly underestimated or overestimated with errors around 5km/h except for SporTrak Pro which had an error

  • 222.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Reliability of GPS based traffic data: an experimental evaluation2014Report (Other academic)
    Abstract [en]

    GPS tracking of mobile objects provides spatial and temporal data for a broad range of applications including traffic management and control, transportation routing and planning. Previous transport research has focused on GPS tracking data as an appealing alternative to travel diaries. Moreover, the GPS based data are gradually becoming a cornerstone for real-time traffic management. Tracking data of vehicles from GPS devices are however susceptible to measurement errors – a neglected issue in transport research. By conducting a randomized experiment, we assess the reliability of GPS based traffic data on geographical position, velocity, and altitude for three types of vehicles; bike, car, and bus. We find the geographical positioning reliable, but with an error greater than postulated by the manufacturer and a non-negligible risk for aberrant positioning. Velocity is slightly underestimated, whereas altitude measurements are unreliable.

  • 223.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Human Geography. Dalarna University, School of Technology and Business Studies, Information Systems.
    Residential planning, driver mobility and CO2 emission2016Report (Other academic)
    Abstract [en]

    In a city there are hotspots that attract the citizens and most of the transportation in the city arises when citizens move between their residence and the hotspots. However, the evaluation between energy-efficient mobility and urban residential planning has been found to be rather weak. In this paper, we propose an ex-ante evaluation method to quantify the impacts in terms of CO2 emissions induced by intra-urban car mobility due to different residential plans implemented at various urban areas. The method is illustrated by a Swedish midsize city which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. On average, the CO2 emissions increase from the continued urban core area (CUCA) to the suburban polycentric area (SPA) to the edge urbanization area (EUA), EUA is almost 3 times more than CUCA. The average travel distances also increase in the same sequence, the overall increase is more than 4 times. Apartment buildings could be more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses.

  • 224.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    Does road network density matter in optimally locating facilities?2015Report (Other (popular science, discussion, etc.))
    Abstract [en]

    Optimal location on the transport infrastructure is the preferable requirement for many decision making processes. Most studies have focused on evaluating performances of optimally locate p facilities by minimizing their distances to a geographically distributed demand (n) when p and n vary. The optimal locations are also sensitive to geographical context such as road network, especially when they are asymmetrically distributed in the plane. The influence of alternating road network density is however not a very well-studied problem especially when it is applied in a real world context. This paper aims to investigate how the density level of the road network affects finding optimal location by solving the specific case of p-median location problem. A denser network is found needed when a higher number of facilities are to locate. The best solution will not always be obtained in the most detailed network but in a middle density level. The solutions do not further improve or improve insignificantly as the density exceeds 12,000 nodes, some solutions even deteriorate. The hierarchy of the different densities of network can be used according to location and transportation purposes and increase the efficiency of heuristic methods. The method in this study can be applied to other location-allocation problem in transportation analysis where the road network density can be differentiated. 

  • 225.
    Zhao, Xiaoyun
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Håkansson, Johan
    Dalarna University, School of Technology and Business Studies, Information Systems. Dalarna University, School of Technology and Business Studies, Human Geography.
    How does the complexity of a road network affect optimal facility locations?2015Report (Other academic)
    Abstract [en]

    The road network is a necessary component in transportation. It facilitiesspatial movements of people and goods, and it also influences the optimal locations of facilities that usually serve as destinations of the movements. To fulfill the transportation needs and to adapt to the facility development, the road network is often organized hierarchically and asymmetrically with various road levels and spatial structures. The complexity of the road network increases along with the increase of road levels and spatial structures. However, location models locate facilities on a given road network, usually the most complex one, and the influence from the complexity of road network in finding optimal locations is not well-studied. This paper aims to investigate how the complexity of a road network affects the optimal facility locations by applying the widely-applied p-median model. The main result indicates that an increase in road network complexity, up to a certain level, can obviously improve the solution, and the complexity beyond that level does not always lead to better solutions. Furthermore, the result is not sensitive to the choice of algorithms. In a specific case study, a detailed sensitivity analysis of algorithm and facility number further provides insight into computation complexity and location problems from intra-urban to inter-urban.

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