Search results for " menetelmä"
showing 10 items of 273 documents
Tavoitteena vahva ja yhtenäinen kansa : historia ja kieli kansallisen identiteetin rakentamisen välineinä Pätsin aikakauden Virossa 1934-1940
2018
In this dissertation, I study national campaigns aimed at constructing Estonian national identity in 1934–1940. The campaigns were organized through the cooperation of Konstantin Päts’ authoritarian government and civil society. I focus on the folk art campaign and on the name changing campaign. The name changing campaign was the largest national project in Estonia, aiming at the Estonification of names. Initially, the campaign focused on changing individuals’ surnames and first names, but later also on changing the names of places, streets and properties. The name changing campaign had history political and language political dimensions. Through the folk art campaign, the state tried to af…
On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction
2020
Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider an approach using a relatively large tolerance for the Markov chain Monte Carlo sampler to ensure its sufficient mixing, and post-processing the output leading to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators, and propose an adaptive approximate Bayesi…
Conditional particle filters with diffuse initial distributions
2020
Conditional particle filters (CPFs) are powerful smoothing algorithms for general nonlinear/non-Gaussian hidden Markov models. However, CPFs can be inefficient or difficult to apply with diffuse initial distributions, which are common in statistical applications. We propose a simple but generally applicable auxiliary variable method, which can be used together with the CPF in order to perform efficient inference with diffuse initial distributions. The method only requires simulatable Markov transitions that are reversible with respect to the initial distribution, which can be improper. We focus in particular on random-walk type transitions which are reversible with respect to a uniform init…
Unbiased Inference for Discretely Observed Hidden Markov Model Diffusions
2021
We develop a Bayesian inference method for diffusions observed discretely and with noise, which is free of discretisation bias. Unlike existing unbiased inference methods, our method does not rely on exact simulation techniques. Instead, our method uses standard time-discretised approximations of diffusions, such as the Euler--Maruyama scheme. Our approach is based on particle marginal Metropolis--Hastings, a particle filter, randomised multilevel Monte Carlo, and importance sampling type correction of approximate Markov chain Monte Carlo. The resulting estimator leads to inference without a bias from the time-discretisation as the number of Markov chain iterations increases. We give conver…
Estimation of causal effects with small data in the presence of trapdoor variables
2021
We consider the problem of estimating causal effects of interventions from observational data when well-known back-door and front-door adjustments are not applicable. We show that when an identifiable causal effect is subject to an implicit functional constraint that is not deducible from conditional independence relations, the estimator of the causal effect can exhibit bias in small samples. This bias is related to variables that we call trapdoor variables. We use simulated data to study different strategies to account for trapdoor variables and suggest how the related trapdoor bias might be minimized. The importance of trapdoor variables in causal effect estimation is illustrated with rea…
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.
Can visualization alleviate dichotomous thinking? Effects of visual representations on the cliff effect
2021
Common reporting styles for statistical results in scientific articles, such as $p$ p -values and confidence intervals (CI), have been reported to be prone to dichotomous interpretations, especially with respect to the null hypothesis significance testing framework. For example when the $p$ p -value is small enough or the CIs of the mean effects of a studied drug and a placebo are not overlapping, scientists tend to claim significant differences while often disregarding the magnitudes and absolute differences in the effect sizes. This type of reasoning has been shown to be potentially harmful to science. Techniques relying on the visual estimation of the strength of evidence have been recom…
Learning cultural literacy through creative practices in schools cultural and multimodal approaches to meaning-making
2022
Introduction: Cultural Literacy and Creativity -- A Sociocultural Approach to Children’s Visual Creations -- Multimodality: Art as a Meaning-Making Process -- Tolerance, Empathy, and Inclusion -- Living Together -- Social Responsibility -- Belonging and Home -- Cultural Literacy During COVID-19 -- Conclusions: Cultural Literacy in Action -- Index. This open access book discusses how cultural literacy can be taught and learned through creative practices. It approaches cultural literacy as a dialogic social process based on learning and gaining knowledge through emphatic, tolerant, and inclusive interaction. The book focuses on meaning-making in children and young people’s visual and multimod…
Diskurssintutkimus - monitieteinen ja monimenetelmäinen ala
2018
There is a growing interest towards metatheoretical examination of linguistic research. This special issue contributes to this examination from the perspective of discourse studies. The issue consists of seven articles which present methods in different areas of discourse studies. The aim of this introductory article is firstly to define the notions of discourse and method. Secondly, through the presentation of the articles of the issue, we present a variety of methods pertaining to different stages of research. In particular, methods of data collection and classification, as well as of data analysis, are presented. We conclude the article with some remarks on the future avenues of the meth…
Ketterät menetelmät ja CMMI: yhteensopivia vai -sopimattomia?
2009
Kuhno, Hanna Maria Ketterät menetelmät ja CMMI: yhteensopivia vai -sopimattomia?/Hanna Kuhno Jyväskylä: Jyväskylän yliopisto, 2009 47 s. Kandidaatintutkielma Tässä tutkielmassa tutustutaan ketterien menetelmien soveltamiseen CMMI (Capability Maturity Model Integration) nimisen prosessien kypsyystasomallin yhteydessä. Tavoitteena on aihealueeseen tutustumisen lisäksi selvittää CMMI:n ja ketterien menetelmien yleisimmät yhteensopivuusongelmat sekä tuoda esille myös niihin kirjallisuudessa esitettyjä ratkaisuja. Niihin CMMI:n alueisiin, jotka ketterät menetelmät täyttävät hyvin, ei tutkielmassa puututa. Ketterät menetelmät ja CMMI mielletään usein toistensa vastakohdiksi, joiden yhteensovitt…