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  • 1.
    Björkström, Anders
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    A two-parametric class of predictors in multivariate regression2007Inngår i: Journal of Chemometrics, ISSN 0886-9383, E-ISSN 1099-128X, Vol. 21, nr 5-6, s. 215-226Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We demonstrate that a number of well-established multivariate regression methods for prediction are related in that they are special cases of basically one general procedure. We try a more general method based on this procedure with two metaparameters. In a simulation study, based on a latent structure model, we compare this method to ridge regression (RR), multivariate partial least squares regression (PLSR) and repeated univariate PLSR. For most types of data sets studied, all methods do approximately equally well. There are some cases where RR and least squares ridge regression (LSRR) yield larger errors than the other methods, and we conclude that one-factor methods are not adequate for situations where more than one latent variable are needed to describe the data. Among those based on latent variables, none of the methods tried is superior to the others in any obvious way.

  • 2.
    Bojarova, Jelena
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Gustafsson, Nils
    Aspects of non-linearities for data assimilation by Kalman filtering in a shallow water modelManuskript (preprint) (Annet vitenskapelig)
  • 3.
    Bojarova, Jelena
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Decomposition of time series of geological data into long and short timescale variation under non-Gaussian state space models2008Rapport (Annet vitenskapelig)
  • 4.
    Bojarova, Jelena
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Non-Gaussian state space models in decomposition of ice core time series in long and short time-scales2010Inngår i: Environmetrics, ISSN 1180-4009, E-ISSN 1099-095X, Vol. 21, nr 6, s. 562-587Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Statistical modelling of six time series of geological ice core chemical data from Greenland is discussed. We decompose the total variation into long time-scale (trend) and short time-scale variations (fluctuations around the trend), and a pure noise component. Too heavy tails of the short-term variation makes a standard time-invariant linear Gaussian model inadequate. We try non-Gaussian state space models, which can be efficiently approximated by time-dependent Gaussian models. In essence, these time-dependent Gaussian models result in a local smoothing, in contrast to the global smoothing provided by the time-invariant model. To describe the mechanism of this local smoothing, we utilise the concept of a local variance function derived from a heavy-tailed density. The time-dependent error variance expresses the uncertainty about the dynamical development of the model state, and it controls the influence of observations on the estimates of the model state components. The great advantage of the derived time-dependent Gaussian model is that the Kalman filter and the Kalman smoother can be used as efficient computational tools for performing the variation decomposition. One of the main objectives of the study is to investigate how the distributional assumption on the model error component of the short time-scale variation affects the decomposition.

  • 5.
    Fetisova, Ekaterina
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Brattström, Gudrun
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Moberg, Anders
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Towards a flexible statistical modelling by latent factors for evaluation of simulated responses to climate forcings: Part IManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Evaluation of climate model simulations is a crucial task in climate research. In a work consisting of three parts, we propose a new statistical framework for evaluation of simulated responses to climate forcings, based on the concept of latent (unobservable) factors. Here, in Part I, we suggest several latent factor models of different complexity that can be used for evaluation of temperature data from climate model simulations against climate proxy data from the last millennium. Each factor model is developed for use with data from a single region, which can be of any size. To be able to test the hypotheses of interest, we have applied the technique of confirmatory factor analysis. We also elucidate the link between our factor models and the statistical methods used in Detection and Attribution (D\&A) studies. In particular, we demonstrate that our factor models can be used as an alternative approach to the methods used in D\&A studies. An additional advantage of their use is that they, in contrast to the commonly used D\&A methods, make it, in principle, possible to investigate whether the forcings of interest act additively or if any interaction effects exist.In Part II we investigate and illustrate the expansion of factor models to structural equation models, which permits the statistical modelling of more complicated climatological relationships. The performance of some of our statistical models suggested in Part I and Part is evaluated and compared in a numerical experiment, whose results are presented in Part III.

  • 6.
    Gummesson, Sara
    et al.
    Stockholms universitet, Humanistiska fakulteten, Institutionen för arkeologi och antikens kultur, Osteoarkeologiska forskningslaboratoriet.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Knutsson, Helena
    Zetterlund, Peter
    Molin, Fredrik
    Knutsson, Kjel
    Lithic Raw Material Economy in the Mesolithic: An Experimental Test of Edged Tool Efficiency and Durability in Bone Tool Production2017Inngår i: Lithic Technology, ISSN 0197-7261, Vol. 42, nr 4, s. 140-154Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The foundation of this paper is lithic economy with a focus on the actual use of different lithic raw materials for tasks at hand. Our specific focus is on the production of bone tools during the Mesolithic. The lithic and osseous assemblages from Strandvägen, Motala, in east-central Sweden provide the archaeological background for the study. Based on a series of experiments we evaluate the efficiency and durability of different tool edges of five lithic raw materials: Cambrian flint, Cretaceous flint, mylonitic quartz, quartz, and porphyry, each used to whittle bone. The results show that flint is the most efficient of the raw materials assessed. Thus, a non-local raw material offers complements of functional characteristics for bone working compared to locally available quartz and mylonitic quartz. This finding provides a new insight into lithic raw material distribution in the region, specifically for bone tool production on site.

  • 7.
    Hind, Alistair
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
    Moberg, Anders
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 2: A pseudo-proxy study addressing the amplitude of solar forcing2012Inngår i: Climate of the Past, ISSN 1814-9324, E-ISSN 1814-9332, Vol. 8, nr 4, s. 1355-1365Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The statistical framework of Part 1 (Sundberg et al., 2012), for comparing ensemble simulation surface temperature output with temperature proxy and instrumental records, is implemented in a pseudo-proxy experiment. A set of previously published millennial forced simulations (Max Planck Institute – COSMOS), including both "low" and "high" solar radiative forcing histories together with other important forcings, was used to define "true" target temperatures as well as pseudo-proxy and pseudo-instrumental series. In a global land-only experiment, using annual mean temperatures at a 30-yr time resolution with realistic proxy noise levels, it was found that the low and high solar full-forcing simulations could be distinguished. In an additional experiment, where pseudo-proxies were created to reflect a current set of proxy locations and noise levels, the low and high solar forcing simulations could only be distinguished when the latter served as targets. To improve detectability of the low solar simulations, increasing the signal-to-noise ratio in local temperature proxies was more efficient than increasing the spatial coverage of the proxy network. The experiences gained here will be of guidance when these methods are applied to real proxy and instrumental data, for example when the aim is to distinguish which of the alternative solar forcing histories is most compatible with the observed/reconstructed climate.

  • 8. Hultin, Emilie
    et al.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Random loss of genetic segments during skin differentiation indicated by analysis of single cells2007Kapittel i bok, del av antologi (Annet vitenskapelig)
  • 9.
    Moberg, Anders
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Grudd, Håkan
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi.
    Hind, Alistair
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi. Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium - Part 3: Practical considerations, relaxed assumptions, and using tree-ring data to address the amplitude of solar forcing2015Inngår i: Climate of the Past, ISSN 1814-9324, E-ISSN 1814-9332, Vol. 11, nr 3, s. 425-448Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A statistical framework for evaluation of climate model simulations by comparison with climate observations from instrumental and proxy data (part 1 in this series) is improved by the relaxation of two assumptions. This allows autocorrelation in the statistical model for simulated internal climate variability and enables direct comparison of two alternative forced simulations to test whether one fits the observations significantly better than the other. The extended framework is applied to a set of simulations driven with forcings for the pre-industrial period 1000-1849 CE and 15 tree-ring-based temperature proxy series. Simulations run with only one external forcing (land use, volcanic, small-amplitude solar, or large-amplitude solar) do not significantly capture the variability in the tree-ring data - although the simulation with volcanic forcing does so for some experiment settings. When all forcings are combined (using either the small- or large-amplitude solar forcing), including also orbital, greenhouse-gas and non-volcanic aerosol forcing, and additionally used to produce small simulation ensembles starting from slightly different initial ocean conditions, the resulting simulations are highly capable of capturing some observed variability. Nevertheless, for some choices in the experiment design, they are not significantly closer to the observations than when unforced simulations are used, due to highly variable results between regions. It is also not possible to tell whether the small-amplitude or large-amplitude solar forcing causes the multiple-forcing simulations to be closer to the reconstructed temperature variability. Proxy data from more regions and of more types, or representing larger regions and complementary seasons, are apparently needed for more conclusive results from model-data comparisons in the last millennium.

  • 10.
    Norén, G. Niklas
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Bate, Andrew
    Edwards, Ralph
    A statistical methodology for drug–drug interaction surveillance2008Inngår i: Statistics in Medicine, ISSN 0277-6715, E-ISSN 1097-0258, Vol. 27, nr 16, s. 3057-3070Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Interaction between drug substances may yield excessive risk of adverse drug reactions (ADRs) when two drugs are taken in combination. Collections of individual case safety reports (ICSRs) related to suspected ADR incidents in clinical practice have proven to be very useful in post-marketing surveillance for pairwise drug–ADR associations, but have yet to reach their full potential for drug–drug interaction surveillance. In this paper, we implement and evaluate a shrinkage observed-to-expected ratio for exploratory analysis of suspected drug–drug interaction in ICSR data, based on comparison with an additive risk model. We argue that the limited success of previously proposed methods for drug–drug interaction detection based on ICSR data may be due to an underlying assumption that the absence of interaction is equivalent to having multiplicative risk factors. We provide empirical examples of established drug–drug interaction highlighted with our proposed approach that go undetected with logistic regression. A database wide screen for suspected drug–drug interaction in the entire WHO database is carried out to demonstrate the feasibility of the proposed approach. As always in the analysis of ICSRs, the clinical validity of hypotheses raised with the proposed method must be further reviewed and evaluated by subject matter experts.

  • 11.
    Persson, Jan-Olov
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. mateamtisk statistik.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. matematisk statistik.
    Multigene analysis can discriminate between ulcerative colitis, Crohn's disease and irritable bowel syndorme2007Rapport (Annet vitenskapelig)
  • 12.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    A classical dataset from Williams, and its role in the study of supersaturated designs.2008Inngår i: Journal of Chemometrics, Vol. 22, s. 436-440Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A Plackett–Burman type dataset from a paper by Williams (1968), with 28 observations and 24 two-level factors, has become a standard dataset for illustrating construction (by halving) of supersaturated designs (SSDs) and for a corresponding data analysis. The aim here is to point out that for several reasons this is an unfortunate situation. The original paper by Williams contains several errors and misprints. Some are in the design matrix, which will here be reconstructed, but worse is an outlier in the response values, which can be observed when data are plotted against the dominating factor. In addition, the data should better be analysed on log-scale than on original scale. The implications of the outlier for SSD analysis are drastic, and it will be concluded that the data should be used for this purpose only if the outlier is properly treated (omitted or modified).

  • 13.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    A note on “shaved dice” inferenceInngår i: American Statistician, ISSN 0003-1305, E-ISSN 1537-2731Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Two dice are rolled repeatedly, only their sum is registered. Have the two dice been “shaved”, so two of the six sides appear more frequently? Pavlides & Perlman (2010) discuss this somewhat complicated type of situation through curved exponen- tial families. Here we contrast their approach by regarding data as incomplete data from a simple exponential family. The latter, supplementary approach is in some respects simpler, it provides additional insight about the relationships among the likelihood equation, Fisher information, and the EM algorithm, and it illustrates the information content in ancillary statistics.

  • 14.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    A Note on Shaved Dice Inference2018Inngår i: American Statistician, ISSN 0003-1305, E-ISSN 1537-2731, Vol. 72, nr 2, s. 155-157Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Two dice are rolled repeatedly, only their sum is registered. Have the two dice been shaved, so two of the six sides appear more frequently? Pavlides and Perlman discussed this somewhat complicated type of situation through curved exponential families. Here, we contrast their approach by regarding data as incomplete data from a simple exponential family. The latter, supplementary approach is in some respects simpler, it provides additional insight about the relationships among the likelihood equation, the Fisher information, and the EM algorithm, and it illustrates the information content in ancillary statistics.

  • 15.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Chemometrics2011Inngår i: International Encyclopedia of Statistical Science / [ed] Miodrag Lovric, Springer , 2011, s. 240-242Kapittel i bok, del av antologi (Fagfellevurdert)
  • 16.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Exponential family models2011Inngår i: International Encyclopedia of Statistical Science / [ed] Miodrag Lovric, Springer , 2011, s. 490-493Kapittel i bok, del av antologi (Fagfellevurdert)
  • 17.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Flat and multimodal likelihoods and model lack of fit in curved exponential families2010Inngår i: Scandinavian Journal of Statistics, ISSN 0303-6898, E-ISSN 1467-9469, Vol. 37, nr 4, s. 632-643Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    It is well known that curved exponential families can have multimodal likelihoods. We investigate the relationship between flat or multimodal likelihoods and model lack of fit, the latter measured by the score (Rao) test statistic of the curved model as embedded in the corresponding full model. When data yield a locally flat or convex likelihood (root of multiplicity >1, terrace point, saddle point, local minimum), we provide a formula for in such points, or a lower bound for it. The formula is related to the statistical curvature of the model, and it depends on the amount of Fisher information. We use three models as examples, including the Behrens-Fisher model, to see how a flat likelihood, etc. by itself can indicate a bad fit of the model. The results are related (dual) to classical results by Efron from 1978.

  • 18.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Kan man lära till statistisk konsult på en kurs?2013Inngår i: Qvintense, ISSN 2000-1819, nr 2, s. 7-9Artikkel i tidsskrift (Annet (populærvitenskap, debatt, mm))
  • 19.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Small sample and selection bias effects in calibration under latent factor regression models2007Inngår i: Journal of Chemometrics, Vol. 21, s. 227-238Artikkel i tidsskrift (Fagfellevurdert)
  • 20.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Statistical consulting2011Inngår i: International Encyclopedia of Statistical Science, Springer , 2011, s. 1390-1392Kapittel i bok, del av antologi (Fagfellevurdert)
  • 21.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Statistical Modelling by Exponential Families2019Bok (Fagfellevurdert)
    Abstract [en]

    This book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful distributions in statistical theory, including the normal, gamma, binomial, Poisson, and negative binomial. Strongly motivated by applications, it presents the essential theory and then demonstrates the theory's practical potential by connecting it with developments in areas like item response analysis, social network models, conditional independence and latent variable structures, and point process models. Extensions to incomplete data models and generalized linear models are also included. In addition, the author gives a concise account of the philosophy of Per Martin-Löf in order to connect statistical modelling with ideas in statistical physics, including Boltzmann's law. Written for graduate students and researchers with a background in basic statistical inference, the book includes a vast set of examples demonstrating models for applications and exercises embedded within the text as well as at the ends of chapters.

  • 22.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Student's t — 100 år2008Inngår i: Qvintensen, nr 4Artikkel i tidsskrift (Annet (populærvitenskap, debatt, mm))
  • 23.
    Sundberg, Rolf
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Feldmann, Uwe
    Exploratory factor analysis-Parameter estimation and scores prediction with high-dimensional data2016Inngår i: Journal of Multivariate Analysis, ISSN 0047-259X, E-ISSN 1095-7243, Vol. 148, s. 49-59Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In an approach aiming at high-dimensional situations, we first introduce a distribution-free approach to parameter estimation in the standard random factor model, that is shown to lead to the same estimating equations as maximum likelihood estimation under normality. The derivation is considerably simpler, and works equally well in the case of more variables than observations (p > n). We next concentrate on the latter case and show results of type: Albeit factor, loadings and specific variances cannot be precisely estimated unless n is large, this is not needed for the factor scores to be precise, but only that p is large; A classical fixed point iteration method can be expected to converge safely and rapidly, provided p is large. A microarray data set, with p = 2000 and n = 22, is used to illustrate this theoretical result.

  • 24.
    Sundberg, Rolf
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Moberg, Anders
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
    Hind, Alistair
    Stockholms universitet, Naturvetenskapliga fakulteten, Institutionen för naturgeografi och kvartärgeologi (INK).
    Statistical framework for evaluation of climate model simulations by use of climate proxy data from the last millennium – Part 1: Theory2012Inngår i: Climate of the Past, ISSN 1814-9324, E-ISSN 1814-9332, Vol. 8, nr 4, s. 1339-1353Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A statistical framework for comparing the output of ensemble simulations from global climate models with networks of climate proxy and instrumental records has been developed, focusing on near-surface temperatures for the last millennium. This framework includes the formulation of a joint statistical model for proxy data, instrumental data and simulation data, which is used to optimize a quadratic distance measure for ranking climate model simulations. An essential underlying assumption is that the simulations and the proxy/instrumental series have a shared component of variability that is due to temporal changes in external forcing, such as volcanic aerosol load, solar irradiance or greenhouse gas concentrations. Two statistical tests have been formulated. Firstly, a preliminary test establishes whether a significant temporal correlation exists between instrumental/proxy and simulation data. Secondly, the distance measure is expressed in the form of a test statistic of whether a forced simulation is closer to the instrumental/proxy series than unforced simulations. The proposed framework allows any number of proxy locations to be used jointly, with different seasons, record lengths and statistical precision. The goal is to objectively rank several competing climate model simulations (e.g. with alternative model parameterizations or alternative forcing histories) by means of their goodness of fit to the unobservable true past climate variations, as estimated from noisy proxy data and instrumental observations.

  • 25.
    Tyrcha, Joanna
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Statistical modelling and saddle point approximation of tail probabilities for accumulated splice loss in fibre optic networks2000Inngår i: J. Applied Statistics, ISSN 0266-4763, Vol. 27, nr 2, s. 245-256Artikkel i tidsskrift (Fagfellevurdert)
  • 26.
    Tyrcha, Joanna
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Lindskog, Peter
    Sundström, Bernt
    Statistical modelling and saddle point approximation of tail probabilities for accumulated splice loss in fibre optic networks1998Rapport (Annet vitenskapelig)
  • 27. von Stein, Petra
    et al.
    Persson, Jan-Olov
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Sundberg, Rolf
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen. Matematisk statistik.
    Multigene analysis can discriminate between ulcerative colitis, Crohn's disease and irritable bowel syndrome2008Inngår i: Gastroenterology, Vol. 134, nr 7, s. 1869-1881Artikkel i tidsskrift (Annet (populærvitenskap, debatt, mm))
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