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  • 1.
    Arvemo, Tobias
    et al.
    University West, School of Business, Economics and IT, Divison of Law, Economics, Statistics and Politics.
    Gråsjö, Urban
    University West, School of Business, Economics and IT, Divison of Law, Economics, Statistics and Politics.
    Employment and Economic Activity in Different Swedish Border Regions2015In: Uddevalla Symposium 2015. Regional Development in an International Context. Regional, National, Cross Border and International Factors for Growth and Development: Revised papers presented at the 18th Uddevalla Symposium, 11-13 June, Sönderborg, Denmark / [ed] Iréne Bernhard, Trollhättan: University West , 2015, p. 45-57Conference paper (Refereed)
    Abstract [en]

    This study investigate how the effect of cross border activities between Sweden and its three Nordic neighbours influence the Swedish local economies along the border using municipal data from 2009. Two measures for the local economies are examined, economic activity (measured by gross pay per inhabitant) and employment rates. The Swedish border regions where divided into four regions: The Swedish border to Finland, The Swedish border to the part of Norway not included in the Oslo labour market, The Swedish border to the Oslo labour market, and the Swedish-Danish border region. The regression models show how the the regions compare to the Swedish average when controlled for market structure and accessibility to population. For Sweden's border regions to Denmark and the Oslo labour market there are significant improvements in both economic activity and employment rates when the border activity is included. The improvement is highest for the Oslo border regions. For the Swedish border to Finland and to the part of Norway not included inte the Olso labour market the border activity has no significant influence on either economic activity or employment rates.

  • 2.
    Arvemo, Tobias
    et al.
    University West, Department of Economics and IT, Division of Law, Politics and Economics.
    Gråsjö, Urban
    University West, Department of Economics and IT, Division of Law, Politics and Economics.
    University Colleges Effect on Municipal Growth in Swedish Middle-sized Municipalities2008In: Uddevalla Symposium 2008: Spatial Dispersed Production and Network Governance: Revised papers presented at the 11th Uddevalla Symposium, 15-17 May, 2008, Kyoto, Japan / [ed] Iréne Bernhard, Trollhättan: University West , 2008, p. 85-98Conference paper (Refereed)
    Abstract [en]

    The main purpose in this paper is to study to what extent accessibility to R&D is an important factor of explaining municipal economic growth. Of special interests is the question whether, the effect of company (private) R&D efforts on economic growth differ if a university college is present in the municipality or not. Therefore the empirical analysis is conducted on a reduced dataset (92 out of 290 municipalities), containing only middle-sized municipalities without traditional ´old´ universities. The idea of the selection process was to find two sets of comparable municipalities with one containing municipalities with university colleges and one with municipalities without university colleges. In the empirical analysis a knowledge production function is estimated with the difference in Gross Municipal Product, GMP, between 1993 and 2001 as the output. In order to account for the importance of proximity, the explanatory variables are expressed as accessibilities to university and company R&D. The total accessibility is then decomposed into local, intra-regional and inter-regional accessibility to R&D. The main results show that local and intra-regional accessibility to company R&D has positive effects on economic growth. On the other hand, local accessibility to university R&D is of no importance, while there are influential effects of intra-regional university R&D. Moreover, the presence of university college R&D activities decreases the importance of the local accessibilitiy to company R&D or put it differently, local accessibility to company R&D is more important in municipalitites without university college activities.

  • 3.
    Eshagh, Mehdi
    et al.
    University West, Department of Engineering Science, Division of Computer, Electrical and Surveying Engineering. Royal Institute of Technology, Division of Geodesy, Stockholm, Sweden .
    Lars E:, Sjöberg
    Royal Institute of Technology, Division of Geodesy, Stockholm, Sweden .
    The modified best quadratic unbiased non-negative estimator (MBQUNE) of variance components2008In: Studia Geophysica et Geodaetica, ISSN 0039-3169, E-ISSN 1573-1626, Vol. 52, no 3, p. 305-320Article in journal (Refereed)
    Abstract [en]

    Estimated variance components may come out as negative numbers without physical meaning. One way out of this problem is to use non-negative methods. Different approaches have been presented for the solution. Sjöberg presented a method of Best Quadratic Unbiased Non-Negative Estimator (BQUNE) in the Gauss-Helmert model. This estimator does not exist in the general case. Here we present the Modified BQUNE (MBQUNE) obtained by a simple transformation from the misclosures used in the BQUE to residuals. In the Gauss-Markov adjustment model the BQUNE and MBQUNE are identical, and they differ in condition and Gauss-Helmert models only by a simple transformation. If the observations are composed of independent/disjunctive groups the MBQUNE exists in any adjustment model and it carries all the properties of the BQUNE (when it exists). The presented variance component models are tested numerically in some simple examples. It is shown that the MBQUNE works well for disjunctive groups of observations.

  • 4.
    Gellerstedt, Martin
    University West, Department of Economics and IT, Division of Computer Science and Informatics.
    M12: Medicinsk statistik 2004 (ed. 1)Book (Other academic)
  • 5.
    Gellerstedt, Martin
    University West, Department of Economics and IT, Division of Computer Science and Informatics.
    Statistiska metoder för kvalitetsutveckling1997 (ed. 1)Book (Other academic)
  • 6.
    Gellerstedt, Martin
    et al.
    University West, Department of Economics and IT, Division of Computer Science and Informatics.
    Svensson, Lars
    University West, Department of Economics and IT, Division of Computer Science and Informatics.
    Www means win win win in education: some experiences from online courses in applied statistics2010In: OZCOTS 2010 Proceedings of the 7th Australian Conferenceon Teaching Statistics / [ed] Helen MacGillivray & Brian Phillips, Statistical society of Australia , 2010, p. 51-56Conference paper (Refereed)
    Abstract [en]

    This paper reports on the experiences from online courses in applied statistics. The courses were designed with the ambition of making studies in statistics, fun, interesting, useful, not that difficult and directly supported the possibility to combine studies and work. When designing the courses we considered three dimensions: "pedagogies","community" and "structure". Experiences after giving a first-year course three times show that the online course succeeds in attracting new studen ts since 90% of the participants would not be able to follow an on-campus course and 62% worked full time.

    The pedagogies were highly appreciated because focusing on the interpretation of results and using computer analyses really changed the prejudices about statistics. Structure and prompt feedback was experienced as important factors. It was possible to combine online studies with employment, and the student completion rate was (84%, 55% and 61%), with a potential for further improvements.

  • 7.
    Kiamehr, Ramin
    et al.
    Department of Geodesy and Geomatics, Zanjan University, Iran.
    Eshagh, Mehdi
    Royal Institute of Technology, Stockholm, Sweden.
    Estimating variance components of ellipsoidal, orthometric and geoidalheights through the GPS/levelling Network in Iran2008In: Journal of the Earth and Space Physics, Vol. 34, no 3, p. 1-13Article in journal (Refereed)
    Abstract [en]

    The Best Quadratic Unbiased Estimation (BQUE) of variance components in the Gauss-Helmert model is used to combine adjustment of GPS/levelling and geoid to determinethe individual variance components for each of the three height types. Through theresearch, different reasons for achievement of the negative variance components werediscussed and a new modified version of the Best Quadratic Unbiased Non-negativeEstimator (MBQUNE) was successfully developed and applied. This estimation could beuseful for estimating the absolute accuracy level which can be achieved using theGPS/levelling method. A general MATLAB function is presented for numericalestimation of variance components by using the different parametric models. Themodified BQUNE and developed software was successfully applied for estimating thevariance components through the sample GPS/levelling network in Iran. In the followingresearch, we used the 75 outlier free and well distributed GPS/levelling data. Threecorrective surface models based on the 4, 5 and 7 parameter models were used throughthe combined adjustment of the GPS/levelling and geoidal heights. Using the 7-parametermodel, the standard deviation indexes of the geoidal, geodetic and orthometric heights inIran were estimated to be about 27, 39 and 35 cm, respectively.

  • 8.
    Tano, Ingrid
    et al.
    University West, Department of Engineering Science, Division of Computer, Electrical and Surveying Engineering.
    Vännman, Kerstin
    Umeå universitet, Umeå, Sverige.
    Comparing Confidence Intervals for Multivariate Process capability Indices2012In: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 28, no 4, p. 481-495Article in journal (Refereed)
    Abstract [en]

    Multivariate process capability indices (MPCIs) are needed for process capability analysis when the quality of a process is determined by several univariate quality characteristics that are correlated. There are several different MPCIs described in the literature, but confidence intervals have been derived for only a handful of these. In practice, the conclusion about process capability must be drawn from a random sample. Hence, confidence intervals or tests for MPCIs are important. With a case study as a start and under the assumption of multivariate normality, we review and compare four different available methods for calculating confidence intervals of MPCIs that generalize the univariate index Cp. Two of the methods are based on the ratio of a tolerance region to a process region, and two are based on the principal component analysis. For two of the methods, we derive approximate confidence intervals, which are easy to calculate and can be used for moderate sample sizes. We discuss issues that need to be solved before the studied methods can be applied more generally in practice. For instance, three of the methods have approximate confidence levels only, but no investigation has been carried out on how good these approximations are. Furthermore, we highlight the problem with the correspondence between the index value and the probability of nonconformance. We also elucidate a major drawback with the existing MPCIs on the basis of the principal component analysis. Our investigation shows the need for more research to obtain an MPCI with confidence interval such that conclusions about the process capability can be drawn at a known confidence level and that a stated value of the MPCI limits the probability of nonconformance in a known way. 

  • 9.
    Tano, Ingrid
    et al.
    University West, Department of Engineering Science, Division of Land Surveying and Mathematics.
    Vännman, Kerstin
    Umeå Universitet & Luleå tekniska universitet & Högskolan Väst.
    Multivariate Process Capability Indices—A New Principal Component Analysis Approach2011In: ENBIS1- Coimbra, Portogal, 2011Conference paper (Refereed)
    Abstract [en]

    Often the quality of a process is determined by several correlated quality characteristics. In such cases the quality characteristic should be treated as a vector and a number of different multivariate process capability indices (MPCI:s) have been developed for such a situation. One of the existing MPCIs described in the literature is based on principal component analysis (PCA). The idea behind this MPCI is to do a PCA and consider only the first few principle components that explain the main part of the variability. Then one of the well-known univariate process capability indices is applied to each selected principle component and thereafter the univariate process capability indices for the selected principle components are combined to one MPCI. In order define this MPCI the tolerance region for the quality characteristic vector is transformed to a separate specification interval for each principal component. Recently it was shown that this transformation of the tolerance region into separate specification intervals is done in an improper way. And it is far from obvious how to obtain the individual specification limits for each selected principal component when the transformation is properly made. This problem gets complicated for 2 principal components and even worse for more than 2 principal components. We propose a new method based on PCA that circumvent these difficulties for the case when the tolerance region is a hyper-rectangular. This method first transforms the original data in a suitable way. Then PCA is done on the transformed data and it is shown that only the first principal component is needed to deem a process as capable or not at a stated significance level. Hence, a multivariate situation is transferred into a univariate situation and well-known theory for univariate process capability indices can be used to draw conclusions about the process capability. The properties of this method are investigated through a simulation study.

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