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We introduce a new fuzzy linear regression method. The method is capable of approximating fuzzy relationships between an independent and a dependent variable. The independent and dependent variables are expected to be a real value and triangular fuzzy numbers, respectively. We demonstrate on twenty datasets that the method is reliable, and it is less sensitive to outliers, compare with possibilistic-based fuzzy regression methods. Unlike other commonly used fuzzy regression methods, the presented method is simple for implementation and it has linear time-complexity. The method guarantees non-negativity of model parameter spreads.

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The aim of the article is to analyze health care expenditures in the Czech Republic compared to selected countries. Expenditures will be analyzed from the point of view of the state and households. The partial aim of the contribution is a correlation analysis to verify the dependency of household healthcare expenditure and average household income in 2010-2015. With the rise of modern technology and knowledge, but also with the extension of human life is constantly growing importance of health care. Over the period 2010-2015, total healthcare spending has risen from CZK 340.7 billion in 2010 to CZK 358.0 billion in 2015. Compared with the development of the GDP, total expenditure on health care (including capital) lagged, and their share of GDP fell from 8.6% to 7.9% in the years above. Household expenditures on health care in the year 2015 amounted to CZK 49,358 million, or 13.8% of the total health care expenditures in the Czech Republic. Using Spearman coefficient was shown dependence of health expenditure of households on their income. At the same time, a forecast for healthcare spending was created for 2 years ahead.

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