https://www.kmacinto.sh/samples daily 0.75 2024-09-09 https://www.kmacinto.sh/samples/reserve-design monthly 0.5 2026-01-23 https://images.squarespace-cdn.com/content/v1/615cae959a714909d76bbc21/1633551513304-ICM9MWUO5D3QX5QSRLX9/bc-bird_comparison.png Samples of Work - Optimizing Reserve Design - Make it stand out Whatever it is, the way you tell your story online can make all the difference. https://www.kmacinto.sh/samples/land-use-change monthly 0.5 2026-01-23 https://images.squarespace-cdn.com/content/v1/615cae959a714909d76bbc21/1633564288359-9UK42VI4PTUZNU7Q4IQ5/Artboard+2.png Samples of Work - Land Use Change Analysis https://images.squarespace-cdn.com/content/v1/615cae959a714909d76bbc21/1633564298804-8YGPQS436ITZZM84X54K/Artboard+2.png Samples of Work - Land Use Change Analysis https://www.kmacinto.sh/samples/language-scores monthly 0.5 2026-01-23 https://images.squarespace-cdn.com/content/v1/615cae959a714909d76bbc21/1633559305417-6M2HVAX6TS2AOKYPLA5V/language-scores.png Samples of Work - Geographically-weighted Regression This map shows the difference in residuals between a global model (Ordinary Least Squares, OLS) and a local model (Geographically Weighted Regression, GWR) for predicting children's language abilities in Vancouver. Areas shaded in pink and green highlight where GWR provides more accurate predictions than OLS, capturing local variations that the global model overlooks. Or, said plainly, pink areas likely represent neighborhoods where factors like income or social context have less impact on children's language abilities than a global model would predict, while green areas indicate neighborhoods where these factors have a stronger impact than expected. https://images.squarespace-cdn.com/content/v1/615cae959a714909d76bbc21/1633560735494-2VZMW5907U19SMPZXBPM/Artboard+2%402x.png Samples of Work - Geographically-weighted Regression GWR takes this idea further by revealing clusters of neighborhoods with similar characteristics, helping us understand why these local variations occur. The second map clusters Vancouver neighborhoods based on factors such as childcare needs, family size, income, lone-parent percentage, and recent immigrant percentage. For example, the red cluster represents areas with high childcare needs and lower average incomes, while the blue cluster shows neighborhoods with higher incomes and fewer lone-parent families. These clusters provide context to the local differences seen in the first map, showing why certain areas respond differently to factors affecting children's language abilities. By understanding these clusters, GWR enables more precise and tailored policy-making, urban planning, and community interventions suited to the unique needs of each neighborhood. https://www.kmacinto.sh/samples/refugee-intake monthly 0.5 2026-01-23 https://images.squarespace-cdn.com/content/v1/615cae959a714909d76bbc21/1633568870306-26X2XT0ZZQUYCY1IU928/Artboard+1%403x.png Samples of Work - Canada’s Refugee Resettlement https://www.kmacinto.sh/km-about daily 1.0 2026-02-13