918 resultados para dynamic factor models


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This thesis examines whether global, local and exchange risks are priced in Scandinavian countries’ equity markets by using conditional international asset pricing models. The employed international asset pricing models are the world capital asset pricing model, the international asset pricing model augmented with the currency risk, and the partially segmented model augmented with the currency risk. Moreover, this research traces estimated equity risk premiums for the Scandinavian countries. The empirical part of the study is performed using generalized method of moments approach. Monthly observations from February 1994 to June 2007 are used. Investors’ conditional expectations are modeled using several instrumental variables. In order to keep system parsimonious the prices of risk are assumed to be constant whereas expected returns and conditional covariances vary over time. The empirical findings of this thesis suggest that the prices of global and local market risk are priced in the Scandinavian countries. This indicates that the Scandinavian countries are mildly segmented from the global markets. Furthermore, the results show that the exchange risk is priced in the Danish and Swedish stock markets when the partially segmented model is augmented with the currency risk factor.

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The growth of breast cancer is regulated by hormones and growth factors. Recently, aberrant fibroblast growth factor (FGF) signalling has been strongly implicated in promoting the progression of breast cancer and is thought to have a role in the development of endocrine resistant disease. FGFs mediate their auto- and paracrine signals through binding to FGF receptors 1-4 (FGFR1-4) and their isoforms. Specific targets of FGFs in breast cancer cells and the differential role of FGFRs, however, are poorly described. FGF-8 is expressed at elevated levels in breast cancer, and it has been shown to act as an angiogenic, growth promoting factor in experimental models of breast cancer. Furthermore, it plays an important role in mediating androgen effects in prostate cancer and in some breast cancer cell lines. We aimed to study testosterone (Te) and FGF-8 regulated genes in Shionogi 115 (S115) breast cancer cells, characterise FGF-8 activated intracellular signalling pathways and clarify the role of FGFR1, -2 and -3 in these cells. Thrombospondin-1 (TSP-1), an endogenous inhibitor of angiogenesis, was recognised as a Te and FGF-8 regulated gene. Te repression of TSP-1 was androgen receptor (AR)-dependent. It required de novo protein synthesis, but it was independent of FGF-8 expression. FGF-8, in turn, downregulated TSP-1 transcription by activating the ERK and PI3K pathways, and the effect could be reversed by specific kinase inhibitors. Differential FGFR1-3 action was studied by silencing each receptor by shRNA expression in S115 cells. FGFR1 expression was a prerequisite for the growth of S115 tumours, whereas FGFR2 expression alone was not able to promote tumour growth. High FGFR1 expression led to a growth advantage that was associated with strong ERK activation, increased angiogenesis and reduced apoptosis, and all of these effects could be reversed by an FGFR inhibitor. Taken together, the results of this thesis show that FGF-8 and FGFRs contribute strongly to the regulation of the growth and angiogenesis of experimental breast cancer and support the evidence for FGF-FGFR signalling as one of the major players in breast cancers.

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In this thesis, general approach is devised to model electrolyte sorption from aqueous solutions on solid materials. Electrolyte sorption is often considered as unwanted phenomenon in ion exchange and its potential as an independent separation method has not been fully explored. The solid sorbents studied here are porous and non-porous organic or inorganic materials with or without specific functional groups attached on the solid matrix. Accordingly, the sorption mechanisms include physical adsorption, chemisorption on the functional groups and partition restricted by electrostatic or steric factors. The model is tested in four Cases Studies dealing with chelating adsorption of transition metal mixtures, physical adsorption of metal and metalloid complexes from chloride solutions, size exclusion of electrolytes in nano-porous materials and electrolyte exclusion of electrolyte/non-electrolyte mixtures. The model parameters are estimated using experimental data from equilibrium and batch kinetic measurements, and they are used to simulate actual single-column fixed-bed separations. Phase equilibrium between the solution and solid phases is described using thermodynamic Gibbs-Donnan model and various adsorption models depending on the properties of the sorbent. The 3-dimensional thermodynamic approach is used for volume sorption in gel-type ion exchangers and in nano-porous adsorbents, and satisfactory correlation is obtained provided that both mixing and exclusion effects are adequately taken into account. 2-Dimensional surface adsorption models are successfully applied to physical adsorption of complex species and to chelating adsorption of transition metal salts. In the latter case, comparison is also made with complex formation models. Results of the mass transport studies show that uptake rates even in a competitive high-affinity system can be described by constant diffusion coefficients, when the adsorbent structure and the phase equilibrium conditions are adequately included in the model. Furthermore, a simplified solution based on the linear driving force approximation and the shrinking-core model is developed for very non-linear adsorption systems. In each Case Study, the actual separation is carried out batch-wise in fixed-beds and the experimental data are simulated/correlated using the parameters derived from equilibrium and kinetic data. Good agreement between the calculated and experimental break-through curves is usually obtained indicating that the proposed approach is useful in systems, which at first sight are very different. For example, the important improvement in copper separation from concentrated zinc sulfate solution at elevated temperatures can be correctly predicted by the model. In some cases, however, re-adjustment of model parameters is needed due to e.g. high solution viscosity.

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The condensation rate has to be high in the safety pressure suppression pool systems of Boiling Water Reactors (BWR) in order to fulfill their safety function. The phenomena due to such a high direct contact condensation (DCC) rate turn out to be very challenging to be analysed either with experiments or numerical simulations. In this thesis, the suppression pool experiments carried out in the POOLEX facility of Lappeenranta University of Technology were simulated. Two different condensation modes were modelled by using the 2-phase CFD codes NEPTUNE CFD and TransAT. The DCC models applied were the typical ones to be used for separated flows in channels, and their applicability to the rapidly condensing flow in the condensation pool context had not been tested earlier. A low Reynolds number case was the first to be simulated. The POOLEX experiment STB-31 was operated near the conditions between the ’quasi-steady oscillatory interface condensation’ mode and the ’condensation within the blowdown pipe’ mode. The condensation models of Lakehal et al. and Coste & Lavi´eville predicted the condensation rate quite accurately, while the other tested ones overestimated it. It was possible to get the direct phase change solution to settle near to the measured values, but a very high resolution of calculation grid was needed. Secondly, a high Reynolds number case corresponding to the ’chugging’ mode was simulated. The POOLEX experiment STB-28 was chosen, because various standard and highspeed video samples of bubbles were recorded during it. In order to extract numerical information from the video material, a pattern recognition procedure was programmed. The bubble size distributions and the frequencies of chugging were calculated with this procedure. With the statistical data of the bubble sizes and temporal data of the bubble/jet appearance, it was possible to compare the condensation rates between the experiment and the CFD simulations. In the chugging simulations, a spherically curvilinear calculation grid at the blowdown pipe exit improved the convergence and decreased the required cell count. The compressible flow solver with complete steam-tables was beneficial for the numerical success of the simulations. The Hughes-Duffey model and, to some extent, the Coste & Lavi´eville model produced realistic chugging behavior. The initial level of the steam/water interface was an important factor to determine the initiation of the chugging. If the interface was initialized with a water level high enough inside the blowdown pipe, the vigorous penetration of a water plug into the pool created a turbulent wake which invoked the chugging that was self-sustaining. A 3D simulation with a suitable DCC model produced qualitatively very realistic shapes of the chugging bubbles and jets. The comparative FFT analysis of the bubble size data and the pool bottom pressure data gave useful information to distinguish the eigenmodes of chugging, bubbling, and pool structure oscillations.

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The objective of this study was to model mathematically and to simulate the dynamic behavior of an auger-type fertilizer applicator (AFA) in order to use the variable-rate application (VRA) and reduce the coefficient of variation (CV) of the application, proposing an angular speed controller θ' for the motor drive shaft. The input model was θ' and the response was the fertilizer mass flow, due to the construction, density of fertilizer, fill factor and the end position of the auger. The model was used to simulate a control system in open loop, with an electric drive for AFA using an armature voltage (V A) controller. By introducing a sinusoidal excitation signal in V A with amplitude and delay phase optimized and varying θ' during an operation cycle, it is obtained a reduction of 29.8% in the CV (constant V A) to 11.4%. The development of the mathematical model was a first step towards the introduction of electric drive systems and closed loop control for the implementation of AFA with low CV in VRA.

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The present study was conducted at the Department of Rural Engineering and the Department of Animal Morphology and Physiology of FCAV/Unesp, Jaboticabal, SP, Brazil. The objective was to verify the influence of roof slope, exposure and roofing material on the internal temperature of reduced models of animal production facilities. For the development of the research, 48 reduced and dissemble models with dimensions 1.00 × 1.00 × 0.50 m were used. The roof was shed-type, and the models faced to the North or South directions, with 24 models for each side of exposure. Ceramic, galvanized-steel and fibro tiles were used to build the roofs. Slopes varied between 20, 30, 40 and 50% for the ceramic tile and 10, 30, 40 and 50% for the other two. Inside the models, temperature readings were performed at every hour, for 12 months. The results were evaluated in a general linear model in a nested 3 × 4 × 2 factorial arrangement, in which the effects of roofing material and exposure were nested on the factor Slope. Means were compared by the Tukey test at 5% of probability. After analyzing the data, we observed that with the increase in the slope and exposure to the South, there was a drop in the internal temperature within the model at the geographic coordinates of Jaboticabal city (SP/Brazil).

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This thesis investigates the effectiveness of time-varying hedging during the financial crisis of 2007 and the European Debt Crisis of 2010. In addition, the seven test economies are part of the European Monetary Union and these countries are in different economical states. Time-varying hedge ratio was constructed using conditional variances and correlations, which were created by using multivariate GARCH models. Here we have used three different underlying portfolios: national equity markets, government bond markets and the combination of these two. These underlying portfolios were hedged by using credit default swaps. Empirical part includes the in-sample and out-of-sample analysis, which are constructed by using constant and dynamic models. Moreover, almost in every case dynamic models outperform the constant ones in the determination of the hedge ratio. We could not find any statistically significant evidence to support the use of asymmetric dynamic conditional correlation model. In addition, our findings are in line with prior literature and support the use of time-varying hedge ratio. Finally, we found that in some cases credit default swaps are not suitable instruments for hedging and they act more as a speculative instrument.

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Cells of epithelial origin, e.g. from breast and prostate cancers, effectively differentiate into complex multicellular structures when cultured in three-dimensions (3D) instead of conventional two-dimensional (2D) adherent surfaces. The spectrum of different organotypic morphologies is highly dependent on the culture environment that can be either non-adherent or scaffold-based. When embedded in physiological extracellular matrices (ECMs), such as laminin-rich basement membrane extracts, normal epithelial cells differentiate into acinar spheroids reminiscent of glandular ductal structures. Transformed cancer cells, in contrast, typically fail to undergo acinar morphogenic patterns, forming poorly differentiated or invasive multicellular structures. The 3D cancer spheroids are widely accepted to better recapitulate various tumorigenic processes and drug responses. So far, however, 3D models have been employed predominantly in the Academia, whereas the pharmaceutical industry has yet to adopt a more widely and routine use. This is mainly due to poor characterisation of cell models, lack of standardised workflows and high throughput cell culture platforms, and the availability of proper readout and quantification tools. In this thesis, a complete workflow has been established entailing well-characterised 3D cell culture models for prostate cancer, a standardised 3D cell culture routine based on high-throughput-ready platform, automated image acquisition with concomitant morphometric image analysis, and data visualisation, in order to enable large-scale high-content screens. Our integrated suite of software and statistical analysis tools were optimised and validated using a comprehensive panel of prostate cancer cell lines and 3D models. The tools quantify multiple key cancer-relevant morphological features, ranging from cancer cell invasion through multicellular differentiation to growth, and detect dynamic changes both in morphology and function, such as cell death and apoptosis, in response to experimental perturbations including RNA interference and small molecule inhibitors. Our panel of cell lines included many non-transformed and most currently available classic prostate cancer cell lines, which were characterised for their morphogenetic properties in 3D laminin-rich ECM. The phenotypes and gene expression profiles were evaluated concerning their relevance for pre-clinical drug discovery, disease modelling and basic research. In addition, a spontaneous model for invasive transformation was discovered, displaying a highdegree of epithelial plasticity. This plasticity is mediated by an abundant bioactive serum lipid, lysophosphatidic acid (LPA), and its receptor LPAR1. The invasive transformation was caused by abrupt cytoskeletal rearrangement through impaired G protein alpha 12/13 and RhoA/ROCK, and mediated by upregulated adenylyl cyclase/cyclic AMP (cAMP)/protein kinase A, and Rac/ PAK pathways. The spontaneous invasion model tangibly exemplifies the biological relevance of organotypic cell culture models. Overall, this thesis work underlines the power of novel morphometric screening tools in drug discovery.

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Modern machine structures are often fabricated by welding. From a fatigue point of view, the structural details and especially, the welded details are the most prone to fatigue damage and failure. Design against fatigue requires information on the fatigue resistance of a structure’s critical details and the stress loads that act on each detail. Even though, dynamic simulation of flexible bodies is already current method for analyzing structures, obtaining the stress history of a structural detail during dynamic simulation is a challenging task; especially when the detail has a complex geometry. In particular, analyzing the stress history of every structural detail within a single finite element model can be overwhelming since the amount of nodal degrees of freedom needed in the model may require an impractical amount of computational effort. The purpose of computer simulation is to reduce amount of prototypes and speed up the product development process. Also, to take operator influence into account, real time models, i.e. simplified and computationally efficient models are required. This in turn, requires stress computation to be efficient if it will be performed during dynamic simulation. The research looks back at the theoretical background of multibody dynamic simulation and finite element method to find suitable parts to form a new approach for efficient stress calculation. This study proposes that, the problem of stress calculation during dynamic simulation can be greatly simplified by using a combination of floating frame of reference formulation with modal superposition and a sub-modeling approach. In practice, the proposed approach can be used to efficiently generate the relevant fatigue assessment stress history for a structural detail during or after dynamic simulation. In this work numerical examples are presented to demonstrate the proposed approach in practice. The results show that approach is applicable and can be used as proposed.

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Fibroblast growth factors (FGFs) are involved in the development and homeostasis of the prostate and other reproductive organs. FGF signaling is altered in prostate cancer. Fibroblast growth factor 8 (FGF8) is a mitogenic growth factor and its expression is elevated in prostate cancer and in premalignant prostatic intraepithelial neoplasia (PIN) lesions. FGF8b is the most transforming isoform of FGF8. Experimental models show that FGF8b promotes several phases of prostate tumorigenesis - including cancer initiation, tumor growth, angiogenesis, invasion and development of bone metastasis. The mechanisms activated by FGF8b in the prostate are unclear. In the present study, to examine the tumorigenic effects of FGF8b on the prostate and other FGF8b expressing organs, an FGF8b transgenic (TG) mouse model was generated. The effect of estrogen receptor beta (ERβ) deficiency on FGF8binduced prostate tumorigenesis was studied by breeding FGF8b-TG mice with ERβ knockout mice (BERKOFVB). Overexpression of FGF8b caused progressive histological and morphological changes in the prostate, epididymis and testis of FGF8b-TG-mice. In the prostate, hyperplastic, preneoplastic and neoplastic changes, including mouse PIN (mPIN) lesions, adenocarcinomas, sarcomas and carcinosarcomas were present in the epithelium and stroma. In the epididymis, a highly cancer-resistant tissue, the epithelium contained dysplasias and the stroma had neoplasias and hyperplasias with atypical cells. Besides similar histological changes in the prostate and epididymis, overexpression of FGF8b induced similar changes in the expression of genes such as osteopontin (Spp1), connective tissue growth factor (Ctgf) and FGF receptors (Fgfrs) in these two tissues. In the testes of the FGF8b-TG mice, the seminiferous epithelium was frequently degenerative and the number of spermatids was decreased. A portion of the FGF8b-TG male mice was infertile. Deficiency of ERβ did not accelerate prostate tumorigenesis in the FGF8b-TG mice, but increased significantly the frequency of mucinous metaplasia and slightly the frequency of inflammation in the prostate. This suggests putative differentiation promoting and anti-inflammatory roles for ERβ. In summary, these results underscore the importance of FGF signaling in male reproductive organs and provide novel evidence for a role of FGF8b in stromal activation and prostate tumorigenesis.

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With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.

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The present review describes recent research on the regulation by glutamate and Ca2+ of the phosphorylation state of the intermediate filament protein of the astrocytic cytoskeleton, glial fibrillary acidic protein (GFAP), in immature hippocampal slices. The results of this research are discussed against a background of modern knowledge of the functional importance of astrocytes in the brain and of the structure and dynamic properties of intermediate filament proteins. Astrocytes are now recognized as partners with neurons in many aspects of brain function with important roles in neural plasticity. Site-specific phosphorylation of intermediate filament proteins, including GFAP, has been shown to regulate the dynamic equilibrium between the polymerized and depolymerized state of the filaments and to play a fundamental role in mitosis. Glutamate was found to increase the phosphorylation state of GFAP in hippocampal slices from rats in the post-natal age range of 12-16 days in a reaction that was dependent on external Ca2+. The lack of external Ca2+ in the absence of glutamate also increased GFAP phosphorylation to the same extent. These effects of glutamate and Ca2+ were absent in adult hippocampal slices, where the phosphorylation of GFAP was completely Ca2+-dependent. Studies using specific agonists of glutamate receptors showed that the glutamate response was mediated by a G protein-linked group II metabotropic glutamate receptor (mGluR). Since group II mGluRs do not act by liberating Ca2+ from internal stores, it is proposed that activation of the receptor by glutamate inhibits Ca2+ entry into the astrocytes and consequently down-regulates a Ca2+-dependent dephosphorylation cascade regulating the phosphorylation state of GFAP. The functional significance of these results may be related to the narrow developmental window when the glutamate response is present. In the rat brain this window corresponds to the period of massive synaptogenesis during which astrocytes are known to proliferate. Possibly, glutamate liberated from developing synapses during this period may signal an increase in the phosphorylation

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Tissue factor is a transmembrane procoagulant glycoprotein and a member of the cytokine receptor superfamily. It activates the extrinsic coagulation pathway, and induces the formation of a fibrin clot. Tissue factor is important for both normal homeostasis and the development of many thrombotic diseases. A wide variety of cells are able to synthesize and express tissue factor, including monocytes, granulocytes, platelets and endothelial cells. Tissue factor expression can be induced by cell surface components of pathogenic microorganisms, proinflammatory cytokines and membrane microparticles released from activated host cells. Tissue factor plays an important role in initiating thrombosis associated with inflammation during infection, sepsis, and organ transplant rejection. Recent findings suggest that tissue factor can also function as a receptor and thus may be important in cell signaling. The present minireview will focus on the role of tissue factor in the pathogenesis of septic shock, infectious endocarditis and invasive aspergillosis, as determined by both in vivo and in vitro models.

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The objective of the present study was to characterize the heart rate (HR) patterns of healthy males using the autoregressive integrated moving average (ARIMA) model over a power range assumed to correspond to the anaerobic threshold (AT) during discontinuous dynamic exercise tests (DDET). Nine young (22.3 ± 1.57 years) and 9 middle-aged (MA) volunteers (43.2 ± 3.53 years) performed three DDET on a cycle ergometer. Protocol I: DDET in steps with progressive power increases of 10 W; protocol II: DDET using the same power values as protocol 1, but applied randomly; protocol III: continuous dynamic exercise protocol with ventilatory and metabolic measurements (10 W/min ramp power), for the measurement of ventilatory AT. HR was recorded and stored beat-to-beat during DDET, and analyzed using the ARIMA (protocols I and II). The DDET experiments showed that the median physical exercise workloads at which AT occurred were similar for protocols I and II, i.e., AT occurred between 75 W (116 bpm) and 85 W (116 bpm) for the young group and between 60 W (96 bpm) and 75 W (107 bpm) for group MA in protocols I and II, respectively; in two MA volunteers the ventilatory AT occurred at 90 W (108 bpm) and 95 W (111 bpm). This corresponded to the same power values of the positive trend in HR responses. The change in HR response using ARIMA models at submaximal dynamic exercise powers proved to be a promising approach for detecting AT in normal volunteers.

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Time series analysis can be categorized into three different approaches: classical, Box-Jenkins, and State space. Classical approach makes a basement for the analysis and Box-Jenkins approach is an improvement of the classical approach and deals with stationary time series. State space approach allows time variant factors and covers up a broader area of time series analysis. This thesis focuses on parameter identifiablity of different parameter estimation methods such as LSQ, Yule-Walker, MLE which are used in the above time series analysis approaches. Also the Kalman filter method and smoothing techniques are integrated with the state space approach and MLE method to estimate parameters allowing them to change over time. Parameter estimation is carried out by repeating estimation and integrating with MCMC and inspect how well different estimation methods can identify the optimal model parameters. Identification is performed in probabilistic and general senses and compare the results in order to study and represent identifiability more informative way.