Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

Two views on interstellar dust: near-infrared scattering and polarized thermal dust emission

Interstellar clouds are not featureless, but show quite complex internal structures of filaments and clumps when observed with high enough resolution. These structures have been generated by 1) turbulent motions driven mainly by supernovae, 2) magnetic fields working on the ions and, through neutral-ion collisions, on neutral gas as well, and 3) self-gravity pulling a dense clump together to form a new star. The study of the cloud structure gives us information on the relative importance of each of these mechanisms, and helps us to gain a better understanding of the details of the star formation process. Interstellar dust is often used as a tracer for the interstellar gas which forms the bulk of the interstellar matter. Some of the methods that are used to derive the column density are summarized in this thesis. A new method, which uses the scattered light to map the column density in large fields with high spatial resolution, is introduced. This thesis also takes a look at the grain alignment with respect to the magnetic fields. The aligned grains give rise to the polarization of starlight and dust emission, thus revealing the magnetic field. The alignment mechanisms have been debated for the last half century. The strongest candidate at present is the radiative torques mechanism. In the first four papers included in this thesis, the scattered light method of column density estimation is formulated, tested in simulations, and finally used to obtain a column density map from observations. They demonstrate that the scattered light method is a very useful and reliable tool in column density estimation, and is able to provide higher resolution than the near-infrared color excess method. These two methods are complementary. The derived column density maps are also used to gain information on the dust emissivity within the observed cloud. The two final papers present simulations of polarized thermal dust emission assuming that the alignment happens by the radiative torques mechanism. We show that the radiative torques can explain the observed decline of the polarization degree towards dense cores. Furthermore, the results indicate that the dense cores themselves might not contribute significantly to the polarized signal, and hence one needs to be careful when interpreting the observations and deriving the magnetic field.

First simultaneous measurement of the top quark mass in the lepton+jets and dilepton channels at CDF

We present a measurement of the mass of the top quark using data corresponding to an integrated luminosity of 1.9fb^-1 of ppbar collisions collected at sqrt{s}=1.96 TeV with the CDF II detector at Fermilab's Tevatron. This is the first measurement of the top quark mass using top-antitop pair candidate events in the lepton + jets and dilepton decay channels simultaneously. We reconstruct two observables in each channel and use a non-parametric kernel density estimation technique to derive two-dimensional probability density functions from simulated signal and background samples. The observables are the top quark mass and the invariant mass of two jets from the W decay in the lepton + jets channel, and the top quark mass and the scalar sum of transverse energy of the event in the dilepton channel. We perform a simultaneous fit for the top quark mass and the jet energy scale, which is constrained in situ by the hadronic W boson mass. Using 332 lepton + jets candidate events and 144 dilepton candidate events, we measure the top quark mass to be mtop=171.9 +/- 1.7 (stat. + JES) +/- 1.1 (syst.) GeV/c^2 = 171.9 +/- 2.0 GeV/c^2.

High-density lipoprotein 17beta-estradiol fatty acyl esters and phytoestrogens : Impact on reverse cholesterol transport and women's cardiovascular health

Reverse cholesterol transport (RCT) is an important function of high-density lipoproteins (HDL) in the protection of atherosclerosis. RCT is the process by which HDL stimulates cholesterol removal from peripheral cells and transports it to the liver for excretion. Premenopausal women have a reduced risk for atherosclerosis compared to age-matched men and there exists a positive correlation for serum 17β-estradiol (E2) and HDL levels in premenopausal women supporting the role of E2 in atherosclerosis prevention. In premenopausal women, E2 associates with HDL as E2 fatty acyl esters. Discovery of the cellular targets, metabolism, and assessment of the macrophage cholesterol efflux potential of these HDL-associated E2 fatty acyl esters were the major objectives of this thesis (study I, III, and IV). Soy phytoestrogens, which are related to E2 in both structure and function, have been proposed to be protective against atherosclerosis but the evidence to support these claims is conflicting. Therefore, another objective of this thesis was to assess the ability of serum from postmenopausal women, treated with isoflavone supplements (compared to placebo), to promote macrophage cholesterol efflux (study II). The scope of this thesis was to cover the roles that HDL-associated E2 fatty acyl esters have in the cellular aspects of RCT and to determine if soy isoflavones can also influence RCT mechanisms. SR-BI was a pivotal cellular receptor, responsible for hepatic and macrophage uptake and macrophage cholesterol efflux potential of HDL-associated E2 fatty acyl esters. Functional SR-BI was also critical for proper LCAT esterification activity which could impact HDL-associated E2 fatty acyl ester assembly and its function. In hepatic cells, LDL receptors also contributed to HDL-associated E2 fatty acyl esters uptake and in macrophage cells, estrogen receptors (ERs) were necessary for both HDL-associated E2 ester-specific uptake and cholesterol efflux potential. HDL-containing E2 fatty acyl esters (E2-FAE) stimulated enhanced cholesterol efflux compared to male HDL (which are deficient in E2) demonstrating the importance of the E2 ester in this process. To support this, premenopausal female HDL, which naturally contains E2, showed greater macrophage cholesterol efflux compared to males. Additionally, hepatic and macrophage cells hydrolyzed the HDL-associated E2 fatty acyl ester into unesterified E2. This could have important biological ramifications because E2, not the esterified form, has potent cellular effects which may influence RCT mechanisms. Lastly, soy isoflavone supplementation in postmenopausal women did not modulate ABCA1-specific macrophage cholesterol efflux but did increase production of plasma pre-β HDL levels, a subclass of HDL. Therefore, the impact of isoflavones on RCT and cardiovascular health needs to be further investigated. Taken as a whole, HDL-associated E2 fatty acyl esters from premenopausal women and soy phytoestrogen treatment in postmenopausal women may be important factors that increase the efficiency of RCT through cellular lipoprotein-related processes and may have direct implications on the cardiovascular health of women.

From a tree to a stand in Finnish boreal forests: biomass estimation and comparison of methods

There is an increasing need to compare the results obtained with different methods of estimation of tree biomass in order to reduce the uncertainty in the assessment of forest biomass carbon. In this study, tree biomass was investigated in a 30-year-old Scots pine (Pinus sylvestris) (Young-Stand) and a 130-year-old mixed Norway spruce (Picea abies)-Scots pine stand (Mature-Stand) located in southern Finland (61º50' N, 24º22' E). In particular, a comparison of the results of different estimation methods was conducted to assess the reliability and suitability of their applications. For the trees in Mature-Stand, annual stem biomass increment fluctuated following a sigmoid equation, and the fitting curves reached a maximum level (from about 1 kg/yr for understorey spruce to 7 kg/yr for dominant pine) when the trees were 100 years old. Tree biomass was estimated to be about 70 Mg/ha in Young-Stand and about 220 Mg/ha in Mature-Stand. In the region (58.00-62.13 ºN, 14-34 ºE, ≤ 300 m a.s.l.) surrounding the study stands, the tree biomass accumulation in Norway spruce and Scots pine stands followed a sigmoid equation with stand age, with a maximum of 230 Mg/ha at the age of 140 years. In Mature-Stand, lichen biomass on the trees was 1.63 Mg/ha with more than half of the biomass occurring on dead branches, and the standing crop of litter lichen on the ground was about 0.09 Mg/ha. There were substantial differences among the results estimated by different methods in the stands. These results imply that a possible estimation error should be taken into account when calculating tree biomass in a stand with an indirect approach.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

Associations of gene polymorphisms and nutrition with calcium homeostasis and bone mineral density : Studies on skeletal nutrigenetics

Heredity explains a major part of the variation in calcium homeostasis and bone strength, and the susceptibility to osteoporosis is polygenetically regulated. Bone phenotype results from the interplay between lifestyle and genes, and several nutritional factors modulate bone health throughout life. Thus, nutrigenetics examining the genetic variation in nutrient intake and homeostatic control is an important research area in the etiology of osteoporosis. Despite continuing progress in the search for candidate genes for osteoporosis, the results thus far have been inconclusive. The main objective of this thesis was to investigate the associations of lactase, vitamin D receptor (VDR), calcium sensing receptor (CaSR) and parathyroid hormone (PTH) gene polymorphisms and lifestyle factors and their interactions with bone health in Finns at varying stages of the skeletal life span. Markers of calcium homeostasis and bone remodelling were measured from blood and urine samples. Bone strength was measured at peripheral and central bone sites. Lifestyle factors were assessed with questionnaires and interviews. Genetic lactase non-persistence (the C/C-13910 genotype) was associated with lower consumption of milk from childhood, predisposing females in particular to inadequate calcium intake. Consumption of low-lactose milk and milk products was shown to decrease the risk for inadequate calcium intake. In young adulthood, bone loss was more common in males than in females. Males with the lactase C/C-13910 genotype may be more susceptible to bone loss than males with the other lactase genotypes, although calcium intake predicts changes in bone mass more than the lactase genotype. The BsmI and FokI polymorphisms of the VDR gene were associated with bone mass in growing adolescents, but the associations weakened with age. In young adults, the A986S polymorphism of the calcium sensing receptor gene was associated with serum ionized calcium concentrations, and the BstBI polymorphism of the parathyroid gene was related to bone strength. The FokI polymorphism and sodium intake showed an interaction effect on urinary calcium excretion. A novel gene-gene interaction between the VDR FokI and PTH BstBI gene polymorphisms was found in the regulation of PTH secretion and urinary calcium excretion. Further research should be carried out with more number of Finns at varying stages of the skeletal life span and more detailed measurements of bone strength. Research should concern mechanisms by which genetic variants affect calcium homeostasis and bone strength, and the role of diet-gene and gene-gene interactions in the pathogenesis of osteoporosis.

Factors affecting farmland prices in Finland

The purpose of the study was to analyse factors affecting the differences in land prices between regions. The key issue was to find out the policy effects on farmland prices. In addition to comprehensive literature review, a theoretical analysis as well as modern panel and spatial econometric techniques were utilized. The study clearly pointed out the importance of taking into account the possible spatial dependence. The data were exceptionally large, comprising more than 6 000 observations. Thus, it allowed a thorough econometric estimation including the possibility to take into account the spatial nature of the data. This study supports the view that there are many other factors that affect farmland prices besides pure agricultural returns. It was also found that the support clearly affects land prices. However, rather than assuming the discount rates for support and market returns to be similar, the rough analysis refers to the discount rate for support being a little lower. If this were true it would indicate that farmers rely more on support income than market returns. The results support the view presented in literature that land values are more responsive to government payments when these payments are perceived to be permanent. An important result of this study is that the structural differences between regions and the structural change in agriculture seemed to have a considerable role in affecting land prices. Firstly, the present structure affects the competition in the land market: the more dense farms are in the region the more there are potential buyers, and the land price increases. Secondly, the change in farm structure (especially in animal husbandry) connected to the policy changes that increase area-based support affects land prices. The effect comes from two sources. Growing farms need more land for the manure, and the proportion of retiring farmers may be lower. The introduction of the manure density variable proved to be an efficient way to aggregate the otherwise very difficult task of taking into account the environmental pressure caused by structural change in animal husbandry. Finally, infrastructure also has a very important role in determining the price level of agricultural land. If other industries are prospering in the surrounding area, agricultural viability also seems to improve. The non-farm opportunities offered to farm families make continuing and developing farming more tempting.

Remote sensing of boreal land cover: estimation of forest attributes and extent

Remote sensing provides methods to infer land cover information over large geographical areas at a variety of spatial and temporal resolutions. Land cover is input data for a range of environmental models and information on land cover dynamics is required for monitoring the implications of global change. Such data are also essential in support of environmental management and policymaking. Boreal forests are a key component of the global climate and a major sink of carbon. The northern latitudes are expected to experience a disproportionate and rapid warming, which can have a major impact on vegetation at forest limits. This thesis examines the use of optical remote sensing for estimating aboveground biomass, leaf area index (LAI), tree cover and tree height in the boreal forests and tundra taiga transition zone in Finland. The continuous fields of forest attributes are required, for example, to improve the mapping of forest extent. The thesis focus on studying the feasibility of satellite data at multiple spatial resolutions, assessing the potential of multispectral, -angular and -temporal information, and provides regional evaluation for global land cover data. Preprocessed ASTER, MISR and MODIS products are the principal satellite data. The reference data consist of field measurements, forest inventory data and fine resolution land cover maps. Fine resolution studies demonstrate how statistical relationships between biomass and satellite data are relatively strong in single species and low biomass mountain birch forests in comparison to higher biomass coniferous stands. The combination of forest stand data and fine resolution ASTER images provides a method for biomass estimation using medium resolution MODIS data. The multiangular data improve the accuracy of land cover mapping in the sparsely forested tundra taiga transition zone, particularly in mires. Similarly, multitemporal data improve the accuracy of coarse resolution tree cover estimates in comparison to single date data. Furthermore, the peak of the growing season is not necessarily the optimal time for land cover mapping in the northern boreal regions. The evaluated coarse resolution land cover data sets have considerable shortcomings in northernmost Finland and should be used with caution in similar regions. The quantitative reference data and upscaling methods for integrating multiresolution data are required for calibration of statistical models and evaluation of land cover data sets. The preprocessed image products have potential for wider use as they can considerably reduce the time and effort used for data processing.

Stochastic Filtering

The stochastic filtering has been in general an estimation of indirectly observed states given observed data. This means that one is discussing conditional expected values as being one of the most accurate estimation, given the observations in the context of probability space. In my thesis, I have presented the theory of filtering using two different kind of observation process: the first one is a diffusion process which is discussed in the first chapter, while the third chapter introduces the latter which is a counting process. The majority of the fundamental results of the stochastic filtering is stated in form of interesting equations, such the unnormalized Zakai equation that leads to the Kushner-Stratonovich equation. The latter one which is known also by the normalized Zakai equation or equally by Fujisaki-Kallianpur-Kunita (FKK) equation, shows the divergence between the estimate using a diffusion process and a counting process. I have also introduced an example for the linear gaussian case, which is mainly the concept to build the so-called Kalman-Bucy filter. As the unnormalized and the normalized Zakai equations are in terms of the conditional distribution, a density of these distributions will be developed through these equations and stated by Kushner Theorem. However, Kushner Theorem has a form of a stochastic partial differential equation that needs to be verify in the sense of the existence and uniqueness of its solution, which is covered in the second chapter.