Search results for "analyysi"
showing 10 items of 1950 documents
Mixture Hidden Markov Models for Sequence Data: The seqHMM Package in R
2019
Sequence analysis is being more and more widely used for the analysis of social sequences and other multivariate categorical time series data. However, it is often complex to describe, visualize, and compare large sequence data, especially when there are multiple parallel sequences per subject. Hidden (latent) Markov models (HMMs) are able to detect underlying latent structures and they can be used in various longitudinal settings: to account for measurement error, to detect unobservable states, or to compress information across several types of observations. Extending to mixture hidden Markov models (MHMMs) allows clustering data into homogeneous subsets, with or without external covariate…
Asymptotic and bootstrap tests for subspace dimension
2022
Most linear dimension reduction methods proposed in the literature can be formulated using an appropriate pair of scatter matrices, see e.g. Ye and Weiss (2003), Tyler et al. (2009), Bura and Yang (2011), Liski et al. (2014) and Luo and Li (2016). The eigen-decomposition of one scatter matrix with respect to another is then often used to determine the dimension of the signal subspace and to separate signal and noise parts of the data. Three popular dimension reduction methods, namely principal component analysis (PCA), fourth order blind identification (FOBI) and sliced inverse regression (SIR) are considered in detail and the first two moments of subsets of the eigenvalues are used to test…
Efficient Bayesian generalized linear models with time-varying coefficients : The walker package in R
2020
The R package walker extends standard Bayesian general linear models to the case where the effects of the explanatory variables can vary in time. This allows, for example, to model the effects of interventions such as changes in tax policy which gradually increases their effect over time. The Markov chain Monte Carlo algorithms powering the Bayesian inference are based on Hamiltonian Monte Carlo provided by Stan software, using a state space representation of the model to marginalise over the regression coefficients for efficient low-dimensional sampling.
Visual Parameter Selection for Spatial Blind Source Separation.
2022
Analysis of spatial multivariate data, i.e., measurements at irregularly-spaced locations, is a challenging topic in visualization and statistics alike. Such data are inteGral to many domains, e.g., indicators of valuable minerals are measured for mine prospecting. Popular analysis methods, like PCA, often by design do not account for the spatial nature of the data. Thus they, together with their spatial variants, must be employed very carefully. Clearly, it is preferable to use methods that were specifically designed for such data, like spatial blind source separation (SBSS). However, SBSS requires two tuning parameters, which are themselves complex spatial objects. Setting these parameter…
Tapaustutkimus Jyväskylä Sinfoniasta
2015
Taidemusiikin markkinointiviestintä ilmiönä ei ole uusi: sen juuret ovat 1800-luvulla alkaneessa taidemusiikin murroksessa. Taidemusiikin markkinointiviestintä on verrattavissa muihin musiikkia koskeviin teksteihin. Keskeistä taidemusiikin markkinoinnissa on se, että musiikkia koskeva tieto halutaan saada siitä kiinnostuneen yleisön keskuuteen. Uutta on kulttuurinen ja teknologinen ympäristö, jossa viestejä lähetetään. Näiden muutosten voisi olettaa vaikuttaneen taidemusiikkia koskevaan markkinointiviestintään. Tämän tutkimuksen tarkoituksena on selvittää, millaista on taidemusiikkia koskeva markkinointiviestintä sosiaalisessa mediassa. Lisäksi halutaan saada selville lähettäjän näkökulma t…
"You helped me out of that darkness" Children as dialogical partners in the collaborative post-family therapy research interview.
2021
Applying Dialogical Methods for Investigations of Happening of Change (DIHC), this study investigated how children who had been diagnosed with an oppositional defiant or conduct disorder participated in a collaborative post‐therapy research interview and talked about their experiences of family therapy. The results showed that the children participated as dialogical partners talking in genuine, emotional, and reflective ways. Encountered as full‐membership partners, the children also co‐constructed meanings for their sensitive experiences. However, their verbal initiatives and responses appeared in very brief moments and could easily have been missed. The collaborative post‐therapy intervie…
Automatic Content Analysis of Computer-Supported Collaborative Inquiry-Based Learning Using Deep Networks and Attention Mechanisms
2020
Computer-supported collaborative inquiry-based learning (CSCIL) represents a form of active learning in which students jointly pose questions and investigate them in technology-enhanced settings. Scaffolds can enhance CSCIL processes so that students can complete more challenging problems than they could without scaffolds. Scaffolding CSCIL, however, would optimally adapt to the needs of a specific context, group, and stage of the group's learning process. In CSCIL, the stage of the learning process can be characterized by the inquiry-based learning (IBL) phase (orientation, conceptualization, investigation, conclusion, and discussion). In this presentation, we illustrate the potential of a…
Stochastic multicriteria evaluation of district heating systems considering the uncertainties
2018
It is of great importance to choose a suitable district heating (DH) system for a specific DH area from the economics, environment and energy (3E) points of view. This is a multicriteria decision making problem, in which the criteria performance values (PVs) and weighting are characterized by uncertain or imprecise information. In this study, seven candidate DH systems are evaluated from the viewpoints of 3E by the stochastic multicriteria acceptability analysis (SMAA) method. SMAA is able to handle the uncertainties of the criteria PVs and the weighting at the same time. These uncertainties are very common and typical in real-life, but in most cases are not treated judiciously or just negl…
Whole-lake experiments reveal the fate of terrestrial particulate organic carbon in benthic food webs of shallow lakes
2014
Lake ecosystems are strongly linked to their terrestrial surroundings by material and energy fluxes across ecosystem boundaries. However, the contribution of terrestrial particulate organic carbon (tPOC) from annual leaf fall to lake food webs has not yet been adequately traced and quantified. In this study, we conducted whole-lake experiments to trace artificially added tPOC through the food webs of two shallow lakes of similar eutrophic status, but featuring alternative stable regimes (macrophyte rich vs. phytoplankton dominated). Lakes were divided with a curtain, and maize (Zea mays) leaves were added, as an isotopically distinct tPOC source, into one half of each lake. To estimate the …
Fourier'n sarjan suppeneminen
2017
Funktion f Fourier'n sarja on ääretön funktiosarja, jossa summataan funktiosta f ja summausindeksistä n riippuvia Fourier'n kertoimia funktiolla e^{inx} kerrottuna. Fourier'n sarjoja käytetään esimerkiksi osittaisdifferentiaaliyhtälöiden ratkaisemiseen. Tässä tutkielmassa käsitellään Fourier'n sarjan suppenemista. Kun Fourier'n sarja keksittiin, pitkään luultiin, että jatkuvan funktion Fourier'n sarja suppenee aina. Tässä työssä osoitetaan, että näin ei ole. Ensin työssä osoitetaan, että jatkuvan funktion Fourier'n sarja "melkein suppenee," eli on Abel- ja Cesàro-summautuva. Abel-summautuvuudessa sarjan summattavat kerrotaan luvulla r^n, missä luku r on itseisarvoltaan pienempi kuin 1 ja n …