Browsing by Author "Dahlbom, Ulla"

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    Least squares estimates of regression functions with certain monotonicity and concavity/convexity restrictions
    (University of Gothenburg, 1998-06-01) Dahlbom, Ulla
    In all regression problems the choice of model and estimation method is due to a priori information about the regression function. In some situations it is motivated to consider regression functions with specific non-parametric characteristics, for instance monotonicity and/or concavity/convexity. We propose a new least squares estimation method for curves that fulfil monotonicity and concavity/convexity restrictions. The least squares estimate of such a regression function is a piecewise linear continuous function with bending points contained in the set of the observed values of the independent variable. The set of bending points, which makes the function a least squares solution can be determined by an iterative algorithm within a finite number of steps.
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    ON TESTS OF EQUIVALENCE
    (University of Gothenburg, 1990-02-01) Holm, Sture; Dahlbom, Ulla
    We will study here a general method for constructing equivalence tests for problems with onedimensional or multidimensional parameter. In the biometric field, the equivalence tests have been studied by many authors under the name of bioequivalence methods. Our general method is closely related to a method for acceptance sampling in the multiparameter case by Berger (1982) and a bioequivalence test method by Schuirmann (1981) for normal distributions and onedimensional parameter. We combine in a general form the ideas of two-sidedness by Schuirmann (1981) and the ideas for multiparameter handling by Berger (1982). We give a number of parametric and nonparametric examples where the general method is used and we illustrate the methods power properties by simulation results.
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    PARAMETRIC AND NONPARAMETRIC TESTS FOR BXOEQUIVALENCE TRIALS
    (University of Gothenburg, 1986-02-01) Dahlbom, Ulla; Holm, Sture
    In pharmacology, comparison of bioavailability is an important problem. A new formulation of a drug is compared with a standard formulation in human subjects. When the extent of absorption is studied the areas under the concentration/time curves (AUC) are the statistics used for analysis. These statistics are determined by some parametric or nonparamatric methods from the basic concentration measurements e. g. every half hour during a day.
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    Variance estimates based on knowledge of monotonicity and concavity properties
    (University of Gothenburg, 1998-08-01) Dahlbom, Ulla
    In problems dealing with regression functions the choice of model and estimation method is due to a priori information about the regression function. In some situations it is motivated to consider regression functions with specific non-parametric characteristics, for instance monotonicity and/or concaVity/convexity. In situations when we only have one y-observation for each Xi we propose two new variance approximation methods, one for curves that fulfil monotonicity restrictions and one for curves that fulfil concavity/ convexity restrictions.