Magnus Ekström

Introducing Gender in Studies on Management Behaviour Among Non-industrial Private Forest Owners

The genderization of non-industrial private forest (NIPF) ownership creates different conditions for male and female forest owners. To compare male and female forest management behaviour and to examine whether observed differences should be understood in terms of gender, data from the Swedish National Board of Forestrys interview inquiry were used. Differences in frequency of harvesting and silvicultural operations were examined by binary logistic regression and differences in harvesting volume were tested by a multiple regression analysis. In all analyses sex of the owner was introduced as one of the explanatory variables. The sex of the owner was found to have a significant effect on the frequency of harvesting, cleaning and supplementary planting, but not on planting and mechanized scarification. In the cases when the sex of the owner was a significant factor, the degree of activity among the female owners was found to be lower. Results regarding harvested volumes did not expose any significant differences in harvesting management strategies between male and female owners.

Multispectral image classification using wavelets: a simulation study

This work presents methods for multispectral image classification using the discrete wavelet transform. Performance of some conventional classification methods is evaluated, through a Monte Carlo study, with or without using the wavelet transform. Spatial autocorrelation is present in the computer-generated data on different scenes, and the misclassification rates are compared. The results indicate that the wavelet-based method performs best among the methods under study.

Temporal variation in air pollution concentrations and preterm birth : a population based epidemiological study

There is growing evidence of adverse birth outcomes due to exposure to air pollution during gestation. However, recent negative studies are also reported. The aim of this study was to assess the effect of ozone and vehicle exhaust exposure (NO2) on the length of the gestational period and risk of preterm delivery. We used data from the Swedish Medical Birth Registry on all vaginally delivered singleton births in the Greater Stockholm area who were conceived during 1987–1995 (n = 115,588). Daily average levels of NO2 (from three measuring stations) and ozone (two stations) were used to estimate trimester and last week of gestation average exposures. Linear regression models were used to assess the association between the two air pollutants and three exposure windows, while logistic regression models were used when analyzing associations with preterm delivery (<37 weeks gestation). Five percent were born preterm. The median gestational period was 40 weeks. Higher levels of ozone during the first trimester were associated with shorter gestation as well as with an elevated risk of preterm delivery, the odds ratio from the most complex model was 1.06 (95% CI: 1.00–1.13) per 10 μg/m3 increase in the mean daily 8-h maximum concentration. Higher levels of ozone during the second trimester were associated with shorter gestation but the elevated risk of preterm delivery was not statistically significant. Higher levels of ozone and NO2 during the last week of gestation were associated with a shorter duration of gestation and NO2 also with preterm delivery. There were no significant associations between first and second trimester NO2 exposure estimates and studied outcomes. The effect of first trimester ozone exposure, known to cause oxidative stress, was smallest among women who conceived during autumn when vitamin D status, important for fetal health, in Scandinavian women is the highest.

Consistency of generalized maximum spacing estimates

General methods for the estimation of distributions can be derived from approximations of certain information measures. For example, both the maximum likelihood (ML) method and the maximum spacing (MSP) method can be obtained from approximations of the Kullback–Leibler information. The ideas behind the MSP method, whereby an estimation method for continuous univariate distributions is obtained from an approximation based on spacings of an information measure, were used by Ranneby & Ekstrom (1997) (using simple spacings) and Ekstrom (1997b) (using high order spacings) to obtain a class of methods, called generalized maximum spacing (GMSP) methods. In the present paper, GMSP methods will be shown to give consistent estimates under general conditions, comparable to those of Bahadur (1971) for the ML method, and those of Shao & Hahn (1999) for the MSP method. In particular, it will be proved that GMSP methods give consistent estimates in any family of distributions with unimodal densities, without any further conditions on the distributions.

Subsampling Methods to Estimate the Variance of Sample Means Based on Nonstationary Spatial Data With Varying Expected Values

Subsampling and block resampling methods have been suggested in the literature to nonparametrically estimate the variance of statistics computed from spatial data. Usually stationary data are required. However, in empirical applications, the assumption of stationarity often must be rejected. This article proposes nonparametric methods to estimate the variance of (functions of) sample means based on nonstationary spatial data using subsampling. We assume that data are observed on a lattice in some region of R2. In the data that we consider, the information in the different picture elements (pixels) of the lattice are allowed to come from different distributions, with smoothly varying expected values, or with expected values decomposed additively into directional components. Furthermore, pixels are assumed to be locally dependent, and the dependence structure is allowed to differ over the lattice. Consistent variance estimators for (functions of) sample means, together with convergence rates in mean square, are provided under these assumptions. An example with applications to forestry, using satellite data, is discussed.

On the consistency of the maximum spacing method

The main result of this paper is a consistency theorem for the maximum spacing method, a general method of estimating parameters in continuous univariate distributions, introduced by Cheng and Amin (J. Roy. Statist. Soc. Ser. A45 (1983) 394–403) and independently by Ranneby (Scand. J. Statist.11 (1984) 93–112). This main result generalizes a theorem of Ranneby (Scand. J. Statist.11 (1984) 93–112). Also, some examples are given, which shows that this estimation method works also in cases where the maximum likelihood method breaks down.

Nonparametric estimation of the variance of sample means based on nonstationary spatial data

ABSTRACT In Politis and Romano (Politis, D.N.; Romano, J.P. Nonparametric Resampling for Homogeneous Strong Mixing Random Fields. Journal of Multivariate Analysis 1993, 47, 301–328.), different block resampling estimators of variance of general linear statistics, e.g., a sample mean, were proposed under the assumption of stationarity. In the present paper such estimators of variance of sample means, computed from nonstationary spatially indexed data , where 𝒜 is a finite subset of the integer lattice , are studied. Consistency of estimators of variance will be shown for the following kind of data: Observations taken from different lattice points are allowed to come from different distributions, and the dependence structure is allowed to differ over the lattice. We assume that all observed values are from distributions with the same expected value, or with expected values that decompose additively into directional components. Furthermore, it will be assumed that observations separated by a certain distance are independent.

Strong limit theorems for sums of logarithms of high order spacings

Several strong limit theorems are proved for sums of logarithms of mth order spacings from general distributions. In all given results, the order mof the spacings is allowed to increase to infinity with the sample size. These results provide a nonparametric strongly consistent estimator of entropy as well as a characterization of the uniform distribution on [0,1]. Furthermore, it is shown that Cressies (1976) goodness of fit test is strongly consistent against all continuous alternatives.

Unrestricted guided transect sampling for surveying sparse species

We present a modification of an earlier presented method using prior auxiliary information in the layout of survey strips. The idea is to imitate a skilled surveyor who purposively seeks the specie ...

Quantifying Spatial Patterns of Landscapes

In this paper we discuss information theoretical landscape indices based on data from digitized maps in grid format: measures based on Shannons entropy, e.g. the measures of diversity and contagion; and measures based on conditional entropy, e.g. a new index which can be seen as an alternative to the measure of contagion that does not have the disadvantage of being highly correlated to the measure of diversity. We also introduce a measurement on how much information is contained in a coarse-scale map about a fine-scale map.